Relevant bibliographies by topics / Bias detection

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Bias detection'

Author: Grafiati
Published: 4 June 2025
Last updated: 15 July 2025

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Journal articles on the topic "Bias detection"

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Khan, Afreen, Anu Chandra, Abbas Ali Mahdi, Syed Tasleem Raza, and Esha Sarkar. "PROSTATE CANCER AND DIABETES: BIOLOGY OR DETECTION BIAS?" Era's Journal of Medical Research 9, no. 2 (2022): 227–38. http://dx.doi.org/10.24041/ejmr2022.36.

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Prostate cancer and diabetes are the two highly prevalent health problems in men worldwide and have a high mortality rates but their association is quite complex and contradictory. This review reported several population based studies which tried to establish a possible association and explains the mechanism by which diabetes exhibits its effect on prostate cancer progression. It also explores the literature around the expression of various receptors and genes which enlightens the possible molecular basis of association and the effect of current antidiabetic drugs like metformin and insulin on the growth and advancement of prostate cancer in diabetic men. Masking of early tumor detection by diabetes might be the possible explanation for the reported inverse association with worse prognosis and shorter survival rate in diabetic prostate cancer patients.
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Galea-Rojas, Manuel, M�rcio V. de Castilho, Heleno Bolfarine, and M�rio de Castro. "Detection of analytical bias." Analyst 128, no. 8 (2003): 1073. http://dx.doi.org/10.1039/b212547a.

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Alshareef, Norah, Xiaohong Yuan, Kaushik Roy, and Mustafa Atay. "A Study of Gender Bias in Face Presentation Attack and Its Mitigation." Future Internet 13, no. 9 (2021): 234. http://dx.doi.org/10.3390/fi13090234.

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In biometric systems, the process of identifying or verifying people using facial data must be highly accurate to ensure a high level of security and credibility. Many researchers investigated the fairness of face recognition systems and reported demographic bias. However, there was not much study on face presentation attack detection technology (PAD) in terms of bias. This research sheds light on bias in face spoofing detection by implementing two phases. First, two CNN (convolutional neural network)-based presentation attack detection models, ResNet50 and VGG16 were used to evaluate the fairness of detecting imposer attacks on the basis of gender. In addition, different sizes of Spoof in the Wild (SiW) testing and training data were used in the first phase to study the effect of gender distribution on the models’ performance. Second, the debiasing variational autoencoder (DB-VAE) (Amini, A., et al., Uncovering and Mitigating Algorithmic Bias through Learned Latent Structure) was applied in combination with VGG16 to assess its ability to mitigate bias in presentation attack detection. Our experiments exposed minor gender bias in CNN-based presentation attack detection methods. In addition, it was proven that imbalance in training and testing data does not necessarily lead to gender bias in the model’s performance. Results proved that the DB-VAE approach (Amini, A., et al., Uncovering and Mitigating Algorithmic Bias through Learned Latent Structure) succeeded in mitigating bias in detecting spoof faces.
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Clementson, David E. "Truth Bias and Partisan Bias in Political Deception Detection." Journal of Language and Social Psychology 37, no. 4 (2017): 407–30. http://dx.doi.org/10.1177/0261927x17744004.

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This study tests the effects of political partisanship on voters’ perception and detection of deception. Based on social identity theory, in-group members should consider their politician’s message truthful while the opposing out-group would consider the message deceptive. Truth-default theory predicts that a salient in-group would be susceptible to deception from their in-group politician. In an experiment, partisan voters in the United States ( N = 618) watched a news interview in which a politician was labeled Democratic or Republican. The politician either answered all the questions or deceptively evaded a question. Results indicated that the truth bias largely prevailed. Voters were more likely to be accurate in their detection when the politician answered and did not dodge. Truth-default theory appears robust in a political setting, as truth bias holds (as opposed to deception bias). Accuracy in detection also depends on group affiliation. In-groups are accurate when their politician answers, and inaccurate when he dodges. Out-groups are more accurate than in-groups when a politician dodges, but still exhibit truth bias.
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Aggarwal, Swati, Tushar Sinha, Yash Kukreti, and Siddarth Shikhar. "Media bias detection and bias short term impact assessment." Array 6 (July 2020): 100025. http://dx.doi.org/10.1016/j.array.2020.100025.

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Yaxley, Richard H., and Rolf A. Zwaan. "Attentional bias affects change detection." Psychonomic Bulletin & Review 12, no. 6 (2005): 1106–11. http://dx.doi.org/10.3758/bf03206451.

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Wang, Lan, Simone M. Weinmann, Gabriella De Lucia, and Xiaohu Yang. "Detection of galaxy assembly bias." Monthly Notices of the Royal Astronomical Society 433, no. 1 (2013): 515–20. http://dx.doi.org/10.1093/mnras/stt743.

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De, Arruda Gabriel, Norton Roman, and Ana Monteiro. "Analysing Bias in Political News." JUCS - Journal of Universal Computer Science 26, no. (2) (2020): 173–99. https://doi.org/10.3897/jucs.2020.011.

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Although of paramount importance to all societies, the fact that media can be biased is a troubling thought to many people. The problem, however, is by no means easy to solve, given its high subjectivity, thereby leading to a number of different approaches by researchers. In this work, we addressed media bias according to a tripartite model whereby news can suffer from a combination of selective coverage of issues (Selection Bias), disproportionate attention given to specific subjects (Coverage Bias), and the favouring of one side in a dispute (Statement Bias). To do so, we approached the problem within an outlier detection framework, defining bias as a noticeable deviation from some mainstream behaviour. Results show that, in following this methodology, one can not only identify bias in specific outlets, but also determine how that bias comes about, how strong it is, and the way it interacts with other dimensions, thereby rendering a more complete picture of the phenomenon under inspection.
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Reiner, Adam J., Justin G. Hollands, and Greg A. Jamieson. "Target Detection and Identification Performance Using an Automatic Target Detection System." Human Factors: The Journal of the Human Factors and Ergonomics Society 59, no. 2 (2016): 242–58. http://dx.doi.org/10.1177/0018720816670768.

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Objective: We investigated the effects of automatic target detection (ATD) on the detection and identification performance of soldiers. Background: Prior studies have shown that highlighting targets can aid their detection. We provided soldiers with ATD that was more likely to detect one target identity than another, potentially acting as an implicit identification aid. Method: Twenty-eight soldiers detected and identified simulated human targets in an immersive virtual environment with and without ATD. Task difficulty was manipulated by varying scene illumination (day, night). The ATD identification bias was also manipulated (hostile bias, no bias, and friendly bias). We used signal detection measures to treat the identification results. Results: ATD presence improved detection performance, especially under high task difficulty (night illumination). Identification sensitivity was greater for cued than uncued targets. The identification decision criterion for cued targets varied with the ATD identification bias but showed a “sluggish beta” effect. Conclusion: ATD helps soldiers detect and identify targets. The effects of biased ATD on identification should be considered with respect to the operational context. Application: Less-than-perfectly-reliable ATD is a useful detection aid for dismounted soldiers. Disclosure of known ATD identification bias to the operator may aid the identification process.
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Wen, Zehao, and Rabih Younes. "ChatGPT v.s. media bias: A comparative study of GPT-3.5 and fine-tuned language models." Applied and Computational Engineering 21, no. 1 (2023): 249–57. http://dx.doi.org/10.54254/2755-2721/21/20231153.

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In our rapidly evolving digital sphere, the ability to discern media bias becomes crucial as it can shape public sentiment and influence pivotal decisions. The advent of large language models (LLMs), such as ChatGPT, noted for their broad utility in various natural language processing (NLP) tasks, invites exploration of their efficacy in media bias detection. Can ChatGPT detect media bias? This study seeks to answer this question by leveraging the Media Bias Identification Benchmark (MBIB) to assess ChatGPT's competency in distinguishing six categories of media bias, juxtaposed against fine-tuned models such as Bidirectional and Auto-Regressive Transformers (BART), Convolutional Bidirectional Encoder Representations from Transformers (ConvBERT), and Generative Pre-trained Transformer 2 (GPT-2). The findings present a dichotomy: ChatGPT performs at par with fine-tuned models in detecting hate speech and text-level context bias, yet faces difficulties with subtler elements of other bias detections, namely, fake news, racial, gender, and cognitive biases.
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Dissertations / Theses on the topic "Bias detection"

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GOMES, RENATA MIRANDA. "BIAS DETECTION IN DEMAND FORECASTING." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2011. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=18477@1.

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COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR<br>PROGRAMA DE SUPORTE À PÓS-GRADUAÇÃO DE INSTS. DE ENSINO<br>Essa dissertação teve como objetivo propor dois novos métodos para detecção de viés na previsão de demanda. Os métodos consistem numa adaptação de duas técnicas de controle estatístico de processos, o gráfico de controle de EWMA e o algoritmo CUSUM, ao contexto de detecção de viés na previsão de demanda. O desempenho dos métodos foi analisado por simulação, para diversos casos de mudança na inclinação (tendência) da série de dados (mudança de modelo constante para modelo com tendência; alteração na tendência de série crescente; estabilização de série crescente em um patamar constante), e com diferentes parâmetros para os métodos. O estudo limitou-se a séries sem sazonalidade e aos métodos de previsão de amortecimento exponencial simples e de Holt. Os resultados mostraram a grande superioridade do gráfico de EWMA proposto e apontam questões para pesquisas futuras.<br>The purpose of this dissertation is to propose two new methods for detection of biases in demand forecasting. These methods are adaptations of two statistical process control techniques, the EWMA control chart and the CUSUM control chart (or CUSUM algorithm), to the context of the detection of biases in demand forecasting. The performance of the proposed methods was analyzed by simulation, for several magnitudes of changes in the trend of the series (change from a level series to a series with a trend, changes in the trend parameter, and stabilization of a series with a trend in a constant average level) and with different parameters for all methods. The study was limited to non-seasonal models and to the methods of simple exponential smoothing and Holt’s Exponential Smoothing. The results have shown the superiority of the EWMA method proposed and indicate issues for future research.
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Lages, Martin. "Bias in visual discrimination and detection." Thesis, University of Oxford, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.298304.

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Trippas, Dries. "Motivated reasoning and response bias : a signal detection approach." Thesis, University of Plymouth, 2013. http://hdl.handle.net/10026.1/2853.

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The aim of this dissertation was to address a theoretical debate on belief bias. Belief bias is the tendency for people to be influenced by their prior beliefs when engaged in deductive reasoning. Deduction is the act of drawing necessary conclusions from premises which are meant to be assumed as true. Given that the logical validity of an argument is independent of its content, being influenced by your prior beliefs in such content is considered a bias. Traditional theories posit there are two belief bias components. Motivated reasoning is the tendency to reason better for arguments with unbelievable conclusions relative to arguments with believable conclusions. Response bias is the tendency to accept believable arguments and to reject unbelievable arguments. Dube et al. (2010) pointed out critical methodological problems that undermine evidence for traditional theories. Using signal detection theory (SDT), they found evidence for response bias only. We adopted the SDT method to compare the viability of the traditional and the response bias accounts. In Chapter 1 the relevant literature is reviewed. In Chapter 2 four experiments which employed a novel SDT-based forced choice reasoning method are presented, showing evidence compatible with motivated reasoning. In Chapter 3 four experiments which used the receiver operating characteristic (ROC) method are presented. Crucially, cognitive ability turned out to be linked to motivated reasoning. In Chapter 4 three experiments are presented in which we investigated the impact of cognitive ability and analytic cognitive style on belief bias, concluding that cognitive style mediated the effects of cognitive ability on motivated reasoning. In Chapter 5 we discuss our findings in light of a novel individual differences account of belief bias. We conclude that using the appropriate measurement method and taking individual differences into account are two key elements to furthering our understanding of belief bias, human reasoning, and cognitive psychology in general.
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Ahmed, Fahad. "Invasive and non-invasive detection of bias temperature instability." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/52227.

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Invasive and non-invasive methods of BTI monitoring and wearout preemption have been proposed. We propose a novel, simple to use, test structure for NBTI /PBTI monitoring. The proposed structure has an AC and a DC stress mode. Although during stress mode, both PMOS and NMOS devices are stressed, the proposed structure isolates the PBTI and NBTI degradation during test mode. A methodology of converting any data-path into ring oscillator (DPRO) is also presented. To avoid the performance overhead of attaching monitoring circuitry to functional block, a non-invasive scheme for BTI monitoring is presented for sleep transistor based logic families. Since, BTI is a critical issue for memories, a scheme for BTI monitoring of 6T SRAM cell based memories is also presented. We make use of the concept of a DPRO and show how a memory system can be made to oscillate in test mode. The frequency of oscillation is a function of the devices in the cell. After validation of the proposed schemes using extensive simulations, we have also validated the results on silicon. We also introduce the concept of wearout mitigation at the compiler level. Using an example of a register file, we present a preemptive method of wearout mitigation using a compiler directed scheme.
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Norman, Dara J. "Quasar-galaxy correlations and the detection of magnification bias /." Thesis, Connect to this title online; UW restricted, 1999. http://hdl.handle.net/1773/5420.

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Hall, Ashley. "Looking Back: An Examination of Hindsight Bias in Change Detection Ability." Marietta College / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=marietta1212840291.

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Dippenaar, Andre. "The Dangers of Speaking a Second Language: An Investigation of Lie Bias and Cognitive Load." Master's thesis, Faculty of Humanities, 2021. http://hdl.handle.net/11427/32623.

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Today's world is an interconnected global village. Communication and business transactions are increasingly conducted in non-native languages. Literature suggests that biases are present when communicating in non-native languages; that a truth bias is present in first language communication, and a lie bias in second language communication. Less than 10% of South Africa's population identifies with English, the lingua franca of the country, as a first language. Not much research in the presence of bias in second language communication has been published in the South African multi-lingual context. This study evaluated the presences of bias within deception frameworks such as the Truth Default State and the veracity effect. This study investigated whether deception detection can be improved by modifying the conditions under which statements are given by placing statement providers under cognitive load. The accuracy of veracity judgment language profiling software, LIWC2015, using published deception language profiles was compared against the results of the participating veracity judges. Results of the study were mixed. It was consistent with extant literature in a presence of a truth bias overall, but mixed in terms of a lie bias. The results supported the Truth Default Theory and veracity effect frameworks. LIWC2015 performed marginally better than human judges in evaluating veracity.
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Johnstone, Kyla Chloe. "Behavioural mechanisms of detection bias in applied ecology and wildlife management." Thesis, The University of Sydney, 2021. https://hdl.handle.net/2123/24944.

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Detecting animals during wildlife surveys underpins the validity of outcomes for pest control, conservation and research. Most surveys rely on animals deciding to engage with a device, hoping the reward outweighs any perceived danger. Animal personality, however, can shape risk-reward decisions by individuals, potentially driving heterogeneity in detection probability and undermining sampling reliability. In this thesis, I investigated personality as a mechanistic driver of detection bias and examined interactions between personality and the risk-reward properties of different survey methods. First, I tested whether high recapture rates equate to low bias. I surveyed the mountain pygmy-possum (Burramys parvus, recapture rate: 0.78-0.92) and found that animals that took greater risks had greater recapture probabilities. I suggest that irrespective of survey assumptions, heterogeneity in response to the perceived risks of a device can drive a bias. Next, I investigated whether a personality bias can differ between methods. I surveyed the military dragon (Ctenophorus isolepis) using noosing and pitfall traps and found that the methods sampled distinctly different personality spectrums. I then examined the interaction between personality and device properties. I surveyed the black rat (Rattus rattus) and exposed populations to novel devices with risk-reward manipulations and found that a personality bias increased with the perceived. Finally, I investigated the transgenerational transfer of personality. I created breeding population of house mice (Mus musculus) with biased personality expressions in founders. However, I found no evidence that offspring reflected founder personality. My findings advance our understanding of how animal behaviour and specifically, personality, acts as a mechanistic driver of detection bias. Strategies to overcome a personality bias should target a board personality spectrum by accounting for the different risk-based decisions animals make.
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Sinclair, Matthew David Maurice. "Microsphere flow quantification and bias detection with a porcine coronary model." Thesis, King's College London (University of London), 2015. http://kclpure.kcl.ac.uk/portal/en/theses/microsphere-flow-quantification-and-bias-detection-with-a-porcine-coronary-model(cd2412bd-3e69-4e70-abc5-ba503fe4af10).html.

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Cardiovascular disease (CVD) is the single largest cause of death in the world, accounting for nearly 30% of mortalities each year. Coronary artery disease (CAD) constitutes the largest category of CVD, and includes diseases caused by plaque formation in the coronary arteries resulting in a range of pathologies including coronary stenosis, ischemia, hibernating myocardium, infarct and heart failure. Clinical dynamic contrast enhanced (DCE) MRI is an emerging non-invasive method for assessing the extent and severity of perfusion defects in the heart. Recently algorithms have been used to quantify myocardial blood flow (MBF) from excised porcine Langendorff hearts under normal flow, low flow, and stress conditions, with validation provided by the microsphere deposition technique. Microspheres of 15 micron diameter deposited within the myocardium were imaged with a fluorescent episcopic cryomicrotome after DCE-MRI acquisition, providing high-resolution images of the heart which were spatially co-registered to the MRI images. Previous validation studies involved physically sectioning hearts into segments for comparison to DCE-MRI. The presented method provided direct correspondence and hence higher accuracy of tissue segments used for the comparative calculation of MBF from DCE-MRI and microspheres. Results of the validation study in 8 pig hearts showed strong correlations at both 1.5T (n = 4) and 3T (n = 4) field strengths, and under all of the experimental flow conditions. A question which has previously arisen regarding the distribution of microspheres in the coronary arterial circulation has been whether they undergo phase separation. Previous to this study geometric information of the coronary arterial structure has not been available for comparison to the distribution of microspheres to determine if this phenomenon plays a role in the observed bias of microspheres relative to a molecular tracer, IDMI. A Poiseuille flow model with an outlet flow boundary condition dependent on perfused tissue mass has been used to simulate flow distribution in a porcine coronary arterial network. The network reconstructed from cryomicrotome imaging data consisted of approximately 105 arterial and arteriolar vessel segments, with a minimum vessel diameter of 0.13mm. A novel analysis using confidence intervals of a binomial distribution at every vascular bifurcation was used to determine the presence of phase separation in the coronary arteries and large arterioles, and to identify the most prevalent locations of phase separation within the network. It is known that phase separation of red blood cells and microspheres occurs in vessels of a diameter similar to that of the particles, namely the small arterioles and capillaries. Results revealed that microsphere phase separation was most prevalent at bifurcations in the conduit coronary arteries, where branching asymmetry was highest. Phase separation prevalence was reduced at arteriolar bifurcations, where branching asymmetry was lower. This is the first study relating coronary arterial geometry with microsphere distributions and serves as an explanation for previously observed microsphere distribution bias in tissue regions of high flow. In future this bias may be corrected using a suitable model, but further work needs to be done to ascertain more accurate terminal vessel boundary conditions.
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Johansson, Moa. "Disgust and fear in detection performance and response biases to threat pictures." Thesis, Stockholm University, Department of Psychology, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-6964.

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<p>Cognitive theories claim that phobias involve unconscious processing and that anxious individuals search the environment for threatening stimuli and therefore detect them more rapidly. However, evidence for this is mixed and suggests that anxious individuals do not detect threat more accurately but are more liberal to report that they detected threat even if there was no actual threat (response bias). In this study, 55 women performed a detection task with pictures of snakes, spiders, and guns. The pictures were backward masked to reduce their visibility. Participants also filled in questionnaires that assessed their fear and disgust. As found in previous studies, detection performance did not correlate with fear. However, inconsistent with previous results, disgust sensitivity correlated with lower detection performance of snakes, and response biases varied with fear of spiders or snakes. These findings provide mixed support for notions of relationships between fear and disgust in threat detection.</p>
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Books on the topic "Bias detection"

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Spinde, Timo. Automated Detection of Media Bias. Springer Fachmedien Wiesbaden, 2025. https://doi.org/10.1007/978-3-658-47798-1.

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Meyerhoff, Hauke S. Linking perceptual animacy to visual attention: An investigation of detection efficiency and attentional bias for chasing objects among distractors kumulative Dissertation. s.n.], 2013.

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Bernards, Neal. Population: Detecting bias. Greenhaven Press, 1992.

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Bernards, Neal. Prisons: Detecting bias. Greenhaven Press, 1990.

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Tipp, Stacey L. Child abuse: Detecting bias. Greenhaven Press, 1991.

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Raymond, Mark R. Detecting and correcting for rater effects in performance assessment. American College Testing Program, 1990.

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New Brunswick. Dept. of Education. Program Development & Implementation Branch., ed. Checklist for detecting bias and stereotyping in instructional materials. Dept. of Education, Province of New Brunswick, 1990.

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Watson, Pamela J. Improved drilling of coal measure rocks for underground mine void detection and exploration programs. U.S. Dept. of the Interior, Bureau of Mines, 1991.

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Watson, Pamela J. Improved drilling of coal measure rocks for underground mine void detection and exploration programs. Bureau of Mines, United States Dept. of the Interior, 1991.

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1951-, Solomon Norman, ed. Unreliable sources: A guide to detecting bias in news media. Carol Pub. Group, 1990.

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Book chapters on the topic "Bias detection"

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Spinde, Timo. "Media Bias." In Automated Detection of Media Bias. Springer Fachmedien Wiesbaden, 2025. https://doi.org/10.1007/978-3-658-47798-1_2.

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Abstract As portrayed in Chap. 1, media bias is a complex concept to identify and analyze. To construct a coherent framework to cover different bias types and to understand the state of the art in computer science when dealing with the domain of media bias is crucial to contribute meaningful research. To do so, in this chapter, we give a more detailed overview about media bias theory, as well as provide the results of an extensive literature review on automated media bias detection methods. To start the journey into this thesis here from a common ground zero, we will briefly summarize the general background of bias first.
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Spinde, Timo. "Neural Media Bias Detection." In Automated Detection of Media Bias. Springer Fachmedien Wiesbaden, 2025. https://doi.org/10.1007/978-3-658-47798-1_6.

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Abstract We already introduced existing methodologies to automatically detect media bias in Chapter 2. We also saw one major example of a traditional feature-based classification system in the previous Chapter 5. Now, we dive more into neural classification within the domain, particularly the major approaches developed during this dissertation.
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Spinde, Timo. "Feature-based Media Bias Detection." In Automated Detection of Media Bias. Springer Fachmedien Wiesbaden, 2025. https://doi.org/10.1007/978-3-658-47798-1_5.

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Abstract Thus far, we have presented a comprehensive literature review on media bias in Chap. 2, evaluated reliable measures for understanding media bias perception in Chap. 3, and introduced our two new datasets, MBIC and BABE, in Chap. 4. We now turn our attention to the design and implementation of automated bias classification systems. This chapter centers on a traditional machine-learning approach grounded on linguistic features.
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Spinde, Timo. "Questionnaire Development." In Automated Detection of Media Bias. Springer Fachmedien Wiesbaden, 2025. https://doi.org/10.1007/978-3-658-47798-1_3.

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Abstract As we laid out in Chap. 2, media bias is a complex concept to identify and analyze. Constructing a coherent framework to cover different bias types has been an important step in setting a basis for future work. However, not only inconsistent definitions of media bias have called for a unified approach; previous assessment strategies of bias are similarly lacking overlap and empirical evaluation.
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Spinde, Timo. "Introduction." In Automated Detection of Media Bias. Springer Fachmedien Wiesbaden, 2025. https://doi.org/10.1007/978-3-658-47798-1_1.

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Abstract This thesis addresses the issue of automatically identifying media bias, mostly linguistic bias, in news articles. A varying word choice in any news content may have a major effect on the public and individual perception of societal issues, especially since regular news consumers are mostly unaware of the degree and scope of bias. Detecting and highlighting media bias is generally a challenging task since it is context-dependent, can be expressed in many ways, and its perception even differs based on personal perception and background.
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Spinde, Timo. "Dataset Creation." In Automated Detection of Media Bias. Springer Fachmedien Wiesbaden, 2025. https://doi.org/10.1007/978-3-658-47798-1_4.

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Abstract At this juncture, we have provided an overview of the media bias domain in Chap. 2, and we have explored how to query the perception of bias in Chap. 3. Nevertheless, we also witnessed the vast array of methods for measuring media bias. This naturally results in an extensive assortment of datasets within the domain.
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Spinde, Timo. "Visualization and Perception of Media Bias." In Automated Detection of Media Bias. Springer Fachmedien Wiesbaden, 2025. https://doi.org/10.1007/978-3-658-47798-1_7.

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Abstract As we discuss throughout the thesis, media bias plays a significant role in shaping individual and collective perceptions of news, which can have profound implications on how people form opinions and make decisions based on the information they consume. In order to address the potential negative consequences of media bias, it is crucial to explore effective communication strategies that can counteract its effects. However, existing research on the theoretical foundations of bias messages and visualizations is limited, with neither visualization theory nor bias theory providing comprehensive insights into effective approaches for addressing this issue within their respective domains.
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Magotra, Varun, Ebrahim Hirani, Vedant Mehta, and Surekha Dholay. "News Bias Detection Using Transformers." In Communication and Intelligent Systems. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2130-8_26.

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Spinde, Timo. "Conclusion and Future Work." In Automated Detection of Media Bias. Springer Fachmedien Wiesbaden, 2025. https://doi.org/10.1007/978-3-658-47798-1_8.

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Abstract This chapter summarizes and concludes the contribution of this thesis in Sect. 8.1 and Section Sect. 8.2, respectively. Sect. 8.3 provides an overview of future work projects and the ethical implications of working on media bias.
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Thougaard, Simon, and Bruce McMillin. "Distributed Bias Detection in Cyber-Physical Systems." In IFIP Advances in Information and Communication Technology. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62840-6_12.

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Conference papers on the topic "Bias detection"

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Krinsky, Joshua, Alan Bettis, Qiuyu Tang, Daniel Moreira, and Aparna Bharati. "Exploring Saliency Bias in Manipulation Detection." In 2024 IEEE International Conference on Image Processing (ICIP). IEEE, 2024. http://dx.doi.org/10.1109/icip51287.2024.10648063.

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Salas-Jimenez, K., Francisco Fernando Lopez-Ponce, Sergio-Luis Ojeda-Trueba, and Gemma Bel-Enguix. "WikiBias as an Extrapolation Corpus for Bias Detection." In Proceedings of the First Workshop on Advancing Natural Language Processing for Wikipedia. Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.wikinlp-1.10.

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Burkhardt, Felix, Bagus Tris Atmaja, Anna Derington, Florian Eyben, and Bjorn Schuller. "Check Your Audio Data: Nkululeko for Bias Detection." In 2024 27th Conference of the Oriental COCOSDA International Committee for the Co-ordination and Standardisation of Speech Databases and Assessment Techniques (O-COCOSDA). IEEE, 2024. https://doi.org/10.1109/o-cocosda64382.2024.10800580.

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Buchmüller, Raphael, Daniel Fürst, Alexander Frings, Udo Schlegel, and Daniel Keim. "Visual Bias Detection for Addressing Illegal Fishing Activities." In 2024 IEEE Visual Analytics Science and Technology VAST Challenge. IEEE, 2024. http://dx.doi.org/10.1109/vastchallenge64683.2024.00009.

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Hossain, Md Mithun, Md Shakil Hossain, Sudipto Chaki, Md Saifur Rahman, and Mohammad Ali Moni. "Bengali Cyberbullying: Detection, Categorization, and Gender Bias Analysis." In 2024 IEEE International Conference on Data Mining Workshops (ICDMW). IEEE, 2024. https://doi.org/10.1109/icdmw65004.2024.00027.

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Kumari, Gitanjali, Anubhav Sinha, and Asif Ekbal. "Unintended Bias Detection and Mitigation in Misogynous Memes." In Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics, 2024. https://doi.org/10.18653/v1/2024.eacl-long.166.

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Chien, Woan-Shiuan, and Chi-Chun Lee. "Understanding Missing Data Bias in Longitudinal Mental Stress Detection." In 2024 IEEE 20th International Conference on Body Sensor Networks (BSN). IEEE, 2024. https://doi.org/10.1109/bsn63547.2024.10780500.

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Dimitrakopoulou, Genny, Nikolaos Kapsalis, and George Kokkinis. "Bias Detection and Correction Methods for Machine Learning Algorithms." In 2024 5th International Conference in Electronic Engineering, Information Technology & Education (EEITE). IEEE, 2024. http://dx.doi.org/10.1109/eeite61750.2024.10654404.

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Gye, Seoyeon, Junwon Ko, Hyounguk Shon, Minchan Kwon, and Junmo Kim. "Reducing the Content Bias for AI-generated Image Detection." In 2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). IEEE, 2025. https://doi.org/10.1109/wacv61041.2025.00049.

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Yi, Wei, and Zhongyang Cheng. "Dielectric Biosensor for E. Coli Detection with DC Bias." In 2024 IEEE Conference on Electrical Insulation and Dielectric Phenomena (CEIDP). IEEE, 2024. https://doi.org/10.1109/ceidp61745.2024.10907533.

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Reports on the topic "Bias detection"

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Reimers, Imke, and Joel Waldfogel. A Framework for Detection, Measurement, and Welfare Analysis of Platform Bias. National Bureau of Economic Research, 2023. http://dx.doi.org/10.3386/w31766.

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Maitongngam, Kritpisut, Varakorn Kosaisavee, and Mathuros Tipayamongkholgul. Antigen detection methods of Opisthorchis viverrini in human: Systematic review and Meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2022. http://dx.doi.org/10.37766/inplasy2022.5.0123.

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Review question / Objective: Research question - Among all of the available antigen methods for Opisthorchis viverrini in human, which one is the most accurate result. Objectives - General objective. To meta-analyze the accuracy of Opisthorchis viverrini antigen detection methods in human. Specific objectives -To compare the overall detection accuracy of Opisthorchis viverrini antigen in humans among FECT and other antigen detection methods -To systematically review Opisthorchis viverrini antigen methods in human -To investigate the effect of bias on the Opisthorchis viverrini antigen detection results in terms of participant selection, index test, reference standard, and flow and timing -To investigate the heterogeneity of the Opisthorchis viverrini antigen detection methods in human. Eligibility criteria: Inclusion criteria 1.1 Research articles related to antigen detection method of Opisthorchis viverrini in humans. 1.2 Research articles in the databases between 2000 - 2021. 2. Exclusion criteriaResearch articles which do not use Formalin Ethyl acetate Concentration Technique (FECT) as the reference standard.
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Kahwati, Leila, Matthew Avenarius, Leslie Brouwer, et al. Blood-Based Tests for Multiple Cancer Screening: A Systematic Review. AHRQ, 2025. https://doi.org/10.23970/ahrqepcsrmultiple.

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Objectives. Screening for multiple cancers in a single blood test is potentially transformative. The objective of this review was to assess the benefits, harms, and accuracy of screening with blood-based multicancer screening tests (MCST) in asymptomatic adults. Data sources. Medline, Cochrane Library, trial registries, relevant government and commercial websites through December 2024; surveillance was conducted through March 31, 2025. Study Selection. Eligible designs included controlled studies for benefit outcomes (e.g., cancer mortality, cancer detection, quality of life), controlled and uncontrolled studies for harm outcomes (e.g., psychosocial distress, adverse events, decrease in standard-of-care screening), and test accuracy studies conducted in external validation populations. Data Extraction and Synthesis. One investigator extracted data and a second checked for accuracy. Two reviewers independently rated risk of bias for included studies using predefined criteria. Results were synthesized narratively. Results. The search yielded 12,043 unique records. No controlled studies evaluated the benefits of screening. One cohort study reported that receipt of standard-of-care lung cancer screening was similar between a group that received the MCST and a group that was eligible but did not receive it (odds ratio, 1.58; 95% CI, 0.47 to 5.31). This same study reported no serious adverse events among the 108 women with false-positive results, but 101 had unnecessary radiation exposure from positron emission tomography–computed tomography scans. Twenty studies (total N=109,177) reported on test accuracy for 19 MCSTs that used various biomarkers (cell-free DNA or RNA, proteins, other) and analytic approaches. Of these, 13 high risk-of-bias studies used case-control designs to estimate sensitivity from cases with known cancer and specificity from cancer-free controls (diagnostic performance). Seven studies (5 high risk of bias, 2 unclear risk of bias) reported prediagnostic performance from testing cancer-free, asymptomatic cohorts with followup over 6 months to 1.5 years to ascertain cancer status. Accuracy outcomes varied widely across tests, subgroups, and study designs. The sensitivity for the detection of cancer ranged from 0.095 to 0.998, specificity ranged from 0.657 to 1.0, and area under the curve (AUC) ranged from 0.52 to 1.0. Sensitivity and AUC were lower in prediagnostic performance studies compared with diagnostic performance studies. Limitations. English-language studies only; heterogeneity precluded quantitative synthesis. Conclusions. We identified no controlled studies of MCSTs that reported on benefits of screening (e.g., mortality, cancer detection, quality of life), though some studies are ongoing. The accuracy of MCSTs varied by test and study design; evidence was insufficient to evaluate harms of screening.
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Canay, Ivan, Magne Mogstad, and Jack Mountjoy. On the Use of Outcome Tests for Detecting Bias in Decision Making. National Bureau of Economic Research, 2020. http://dx.doi.org/10.3386/w27802.

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Hawley. PR-015-11707-R01 Test Diagnostic Methods for Turbine Gas Meters. Pipeline Research Council International, Inc. (PRCI), 2013. http://dx.doi.org/10.55274/r0010671.

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Similar to most metering technologies, turbine meters are known to be affected by abnormal flow or abnormal mechanical conditions which can cause bias in flow measurement. These types of flow conditions include blockage at the flow meter or straightening vanes, grime or liquid contamination on the internal meter components, damage to the internal meter components, and pulsation in the flow. With the introduction of ultrasonic and Coriolis meters for gas applications, the natural gas industry has embraced the concept of meters with embedded diagnostic capabilities. These capabilities allow the detection of potential problems with the flow behavior or meter condition that may lead to measurement error. Diagnostic measurements also exist for turbine meters. Some turbine meter manufacturers provide techniques for diagnosing proper meter performance through approaches that include unique design attributes (e.g., dual-rotors) or by monitoring the characteristics (shape, timing, etc.) of the pulses produced as blades pass a sensor. Various analog and digital signal analysis methods exist to interpret the output pulse characteristics to determine meter condition attributes such as bent blades and bearing wear. The objective of this research was to assess, through flow testing, the ability of various diagnostic methods to detect abnormal flow and abnormal mechanical conditions for both single and dual-rotor turbine meters. A secondary objective was to determine the amount of flow measurement error that could be present for the various flow conditions that were tested. The approach was to test three different diagnostic methods on a single-rotor and dual-rotor turbine meter at the Metering Research Facility at Southwest Research Institute. The selected diagnostic methods were the Smith MeterTM AccuLERT II from FMC Technologies, TurbinScope from Elster-Instromet, and The Turbo Corrector from Mercury Instruments. Tests were performed under controlled conditions and were designed to determine the ability of the selected diagnostics to detect various levels of flow meter or tube bundle blockage, grime buildup on the rotor or rotor bearings, damage to the rotor, or flow pulsations.
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Kleman, Isabella. Onion storage diseases and their headspace volatiles. Faculty of Landscape Architecture, Horticulture and Crop Production Science, Swedish University of Agricultural Sciences, 2023. http://dx.doi.org/10.54612/a.602791tdo5.

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Onion, Allium cepa, is one of the world’s most commonly produced and consumed vegetables. In order to be available year round in temperate climates onions must be stored for several months. During this time parts of the harvested weight of bulbs are lost to storage diseases, sprouting and respiration leading to loss of carbohydrates and water. Diseases developing in storage may be difficult to spot at early stages as bulbs are typically stored in large bins. However, storage diseases can change the volatile metabolite profile of the infected onions. Electronic sensors that detect the concentration of specific volatile compounds in the air could be deployed in storage facilities to detect these changes. This would provide an early warning system that could detect diseases developing in storage bins before it becomes obvious to a human observer. In this way, some of the losses that occur during storage of onions could be prevented. This introductory paper discusses some of the available literature on the facets of onion production that are connected to storage disease development and the detection of said storage diseases using headspace sampling and analysis. The focus of the paper is mainly on onion production and storage of long day cultivars in relatively cold, temperate climates, as the use of short day cultivars and warm storage in warmer climates comes with different challenges and diseases.
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CT Lung Densitometry, Consensus QIBA Profile. Chair Charles Hatt and Miranda Kirby. • The Publisher is Radiological Society of North America (RSNA)/Quantitative Imaging Biomarkers Alliance (QIBA), 2020. https://doi.org/10.1148/qiba/20200904.

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The goal of a QIBA Profile is to achieve a repeatable and useful level of performance for measures of lung density from quantitative CT using the RA-950 HU and Perc15 biomarkers of emphysema. Please see Appendix C for more detailed information on the calculation of and rationale for RA-950 HU and Perc15 as the biomarkers of choice. The Claim (Section 2) describes the performance in terms of bias and precision of RA-950 HU and Perc15 for detecting change in lung density. The Activities (Section 3) describe how to generate RA-950 HU and Perc15 for longitudinal studies of the change in lung density. Requirements are placed on the Actors that participate in those activities as necessary to achieve the Claim in Section 2. Assessment Procedures (Section 4) for evaluating specific requirements are defined as needed. This QIBA Profile (CT: Lung Densitometry) addresses RA-950 HU and Perc15 for longitudinal studies which are often used as biomarkers of emphysema progression in chronic obstructive pulmonary disease (COPD) or as a response to cessation of smoking and possible future treatment approaches. It places requirements on Acquisition Devices, Physicists, Technologists, Clinicians, Statisticians, Reconstruction Software and Image Analysis Software involved in Product Qualification, Staff Qualification, Periodic Quality Assurance, Subject Handling, Protocol Design, Image Data Acquisition, Image Data Reconstruction, Image QA, Image Distribution and Image Analysis. The requirements are focused on achieving negligible bias and avoiding unnecessary variability of the RA-950 HU and Perc15 measurements by compensating for variations in CT number due to inconsistency of lung inflation volume and calibration of the CT scanner, and vendor-specific bias due to CT scanner make and model. To meet the claims, scanner calibration is performed using a well characterized imaging phantom ideally containing lung equivalent density foams as described in Section 4.1. The clinical performance targets are to achieve bias and repeatability such that a change in RA950 HU of ≥ 3.7% of the normalized lung volume, or a change in Perc15 of ≥ 11 HU after lung volume adjustment can be accepted as indicative of a true change (with 95% confidence). This document is intended to help clinicians basing decisions on these biomarkers, imaging staff generating these biomarkers, vendor staff developing related products, purchasers of such products and investigators designing trials with imaging endpoints. Note that this document only states requirements to achieve the claim, not “requirements for standard of care.” Conformance to this Profile is less important than providing appropriate patient care. The compilation of this document represents the efforts of many individuals over a several years of effort, some but not all of whom are acknowledged in Appendix A. QIBA Profiles addressing other imaging biomarkers using CT, MRI, PET and Ultrasound can be found at qibawiki.rsna.org.
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Treadwell, Jonathan R., James T. Reston, Benjamin Rouse, Joann Fontanarosa, Neha Patel, and Nikhil K. Mull. Automated-Entry Patient-Generated Health Data for Chronic Conditions: The Evidence on Health Outcomes. Agency for Healthcare Research and Quality (AHRQ), 2021. http://dx.doi.org/10.23970/ahrqepctb38.

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Background. Automated-entry consumer devices that collect and transmit patient-generated health data (PGHD) are being evaluated as potential tools to aid in the management of chronic diseases. The need exists to evaluate the evidence regarding consumer PGHD technologies, particularly for devices that have not gone through Food and Drug Administration evaluation. Purpose. To summarize the research related to automated-entry consumer health technologies that provide PGHD for the prevention or management of 11 chronic diseases. Methods. The project scope was determined through discussions with Key Informants. We searched MEDLINE and EMBASE (via EMBASE.com), In-Process MEDLINE and PubMed unique content (via PubMed.gov), and the Cochrane Database of Systematic Reviews for systematic reviews or controlled trials. We also searched ClinicalTrials.gov for ongoing studies. We assessed risk of bias and extracted data on health outcomes, surrogate outcomes, usability, sustainability, cost-effectiveness outcomes (quantifying the tradeoffs between health effects and cost), process outcomes, and other characteristics related to PGHD technologies. For isolated effects on health outcomes, we classified the results in one of four categories: (1) likely no effect, (2) unclear, (3) possible positive effect, or (4) likely positive effect. When we categorized the data as “unclear” based solely on health outcomes, we then examined and classified surrogate outcomes for that particular clinical condition. Findings. We identified 114 unique studies that met inclusion criteria. The largest number of studies addressed patients with hypertension (51 studies) and obesity (43 studies). Eighty-four trials used a single PGHD device, 23 used 2 PGHD devices, and the other 7 used 3 or more PGHD devices. Pedometers, blood pressure (BP) monitors, and scales were commonly used in the same studies. Overall, we found a “possible positive effect” of PGHD interventions on health outcomes for coronary artery disease, heart failure, and asthma. For obesity, we rated the health outcomes as unclear, and the surrogate outcomes (body mass index/weight) as likely no effect. For hypertension, we rated the health outcomes as unclear, and the surrogate outcomes (systolic BP/diastolic BP) as possible positive effect. For cardiac arrhythmias or conduction abnormalities we rated the health outcomes as unclear and the surrogate outcome (time to arrhythmia detection) as likely positive effect. The findings were “unclear” regarding PGHD interventions for diabetes prevention, sleep apnea, stroke, Parkinson’s disease, and chronic obstructive pulmonary disease. Most studies did not report harms related to PGHD interventions; the relatively few harms reported were minor and transient, with event rates usually comparable to harms in the control groups. Few studies reported cost-effectiveness analyses, and only for PGHD interventions for hypertension, coronary artery disease, and chronic obstructive pulmonary disease; the findings were variable across different chronic conditions and devices. Patient adherence to PGHD interventions was highly variable across studies, but patient acceptance/satisfaction and usability was generally fair to good. However, device engineers independently evaluated consumer wearable and handheld BP monitors and considered the user experience to be poor, while their assessment of smartphone-based electrocardiogram monitors found the user experience to be good. Student volunteers involved in device usability testing of the Weight Watchers Online app found it well-designed and relatively easy to use. Implications. Multiple randomized controlled trials (RCTs) have evaluated some PGHD technologies (e.g., pedometers, scales, BP monitors), particularly for obesity and hypertension, but health outcomes were generally underreported. We found evidence suggesting a possible positive effect of PGHD interventions on health outcomes for four chronic conditions. Lack of reporting of health outcomes and insufficient statistical power to assess these outcomes were the main reasons for “unclear” ratings. The majority of studies on PGHD technologies still focus on non-health-related outcomes. Future RCTs should focus on measurement of health outcomes. Furthermore, future RCTs should be designed to isolate the effect of the PGHD intervention from other components in a multicomponent intervention.
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Weissinger, Rebecca. Evaluation of hanging-garden endemic-plant monitoring at Southeast Utah Group national parks, 2013–2020. Edited by Alice Wondrak Biel. National Park Service, 2022. http://dx.doi.org/10.36967/2294868.

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Hanging gardens are the most common type of spring at Arches National Park (NP) and Natural Bridges National Monument (NM). They are also present at Canyonlands National Park, but hanging gardens are rare off the Colorado Plateau. Their cliffside setting provides stable access to water without flood disturbance. This combination provides unique habitat that is rich in endemic plant species. The diffuse, seeping emergence of water makes measuring springflow impossible at most sites. Park managers have an interest in monitoring hanging gardens—especially as the climate warms and aridity and water demand both increase. The Northern Colorado Plateau Net-work (NCPN) proposed methods for monitoring seven perennial endemic-plant species at hanging gardens as indicators of spring health and proxies for water availability. Because hanging gardens occur on bedrock outcrops, systematic or random sampling was not possible due to safety concerns and potential resource damage on steep, wet slopes. Examining eight years (2013–2020) of data, this report evaluates the suitability of endemic-plant count data at hanging gardens as a monitoring indicator. It also provides our first evaluation of status and trends at NCPN hanging gardens. The seven species included in monitoring were Rydberg’s thistle (Cirsium rydbergii), Kachina daisy (Erigeron kachinensis), alcove death camas (Zigadenus vaginatus), alcove bog orchid (Habenaria zothecina), cave primrose (Primula specuicola), alcove columbine (Aquilegia micrantha), and Eastwood’s monkeyflower (Mimulus eastwoodiae). Six of the seven species were found at each park. Up to 500 individuals of each species were counted at 42 hanging gardens in Arches NP, 14 hanging gardens in Natural Bridges NM, and 3 hanging gardens in Canyonlands NP. Larger populations were divided into count classes of 501–1,000, 1,001–10,000, and more than 10,000 individuals. Counts from two independent observers and from back-to-back years of sampling were compared for repeatability. Repeatability in count classes was less than 50% for Kachina daisy and Eastwood’s monkeyflower, which both propagate vegetatively via ramets and/or stolons. Repeatability was greater than 90% for only one species, Rydberg’s thistle. The remaining species were categorized in different classes between 15–40% of the time. Independent-observer comparisons were only available for 6.6% of the dataset, but these observations suggested that (1) observer bias was present and (2) the observer with more experience working in hanging gardens generally had higher counts than the observer with less experience in this system. Although repeatability was variable, it was within the range reported by other studies for most species. The NCPN, in discussion with park staff, has elected to make some modifications to the protocol but will continue using endemic plant counts as an indicator of hanging-garden health to maintain a biological variable as a complement to our physical-response data. This is due to their high value to park biodiversity and the difficulty of developing a more robust approach to monitoring in these sites. Endemic-plant monitoring will continue for the five species with the highest repeatability during pilot monitoring and will focus on detecting changes in smaller populations. Most hanging gardens have more than one endemic species present, so several populations can be tracked at each site. Our period of record is relatively brief, and the distribution of endemic-plant populations in different count classes at these sites has not yet shown any statistical trends over time. Be-cause of the large count classes, our methods are more sensitive to showing change in smaller populations (fewer than 500 individuals). Small populations are also of greatest concern to park managers because of their vulnerability to declines or extirpation due to drought. Over-all, more sites had endemic-plant populations of fewer than 100 individuals at the end...
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