Relevant bibliographies by topics / Subgroups Identification

Contents

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

Academic literature on the topic 'Subgroups Identification'

Author: Grafiati
Published: 14 March 2023
Last updated: 31 July 2025

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Journal articles on the topic "Subgroups Identification"

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Lipponen, Jukka, Klaus Helkama, and Milla Juslin. "Subgroup Identification, Superordinate Identification and Intergroup Bias between the Subgroups." Group Processes & Intergroup Relations 6, no. 3 (2003): 239–50. http://dx.doi.org/10.1177/13684302030063002.

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Yang, Hanlu, Trung Vu, Qunfang Long, Vince Calhoun, and Tülay Adali. "Identification of Homogeneous Subgroups from Resting-State fMRI Data." Sensors 23, no. 6 (2023): 3264. http://dx.doi.org/10.3390/s23063264.

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The identification of homogeneous subgroups of patients with psychiatric disorders can play an important role in achieving personalized medicine and is essential to provide insights for understanding neuropsychological mechanisms of various mental disorders. The functional connectivity profiles obtained from functional magnetic resonance imaging (fMRI) data have been shown to be unique to each individual, similar to fingerprints; however, their use in characterizing psychiatric disorders in a clinically useful way is still being studied. In this work, we propose a framework that makes use of f
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Hayashi, M., A. Kawachi, and H. Kobayashi. "Quantum measurements for hidden subgroup problems with optimal sample complexity." Quantum Information and Computation 8, no. 3&4 (2008): 345–58. http://dx.doi.org/10.26421/qic8.3-4-8.

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One of the central issues in the hidden subgroup problem is to bound the sample complexity, i.e., the number of identical samples of coset states sufficient and necessary to solve the problem. In this paper, we present general bounds for the sample complexity of the identification and decision versions of the hidden subgroup problem. As a consequence of the bounds, we show that the sample complexity for both of the decision and identification versions is $\Theta(\log|\HH|/\log p)$ for a candidate set $\HH$ of hidden subgroups in the case \REVISE{where the candidate nontrivial subgroups} have t
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Khadirnaikar, Seema, Sudhanshu Shukla, and S. R. M. Prasanna. "Integration of pan-cancer multi-omics data for novel mixed subgroup identification using machine learning methods." PLOS ONE 18, no. 10 (2023): e0287176. http://dx.doi.org/10.1371/journal.pone.0287176.

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Cancer is a heterogeneous disease, and patients with tumors from different organs can share similar epigenetic and genetic alterations. Therefore, it is crucial to identify the novel subgroups of patients with similar molecular characteristics. It is possible to propose a better treatment strategy when the heterogeneity of the patient is accounted for during subgroup identification, irrespective of the tissue of origin. This work proposes a machine learning (ML) based pipeline for subgroup identification in pan-cancer. Here, mRNA, miRNA, DNA methylation, and protein expression features from pa
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Seibold, Heidi, Achim Zeileis, and Torsten Hothorn. "Model-Based Recursive Partitioning for Subgroup Analyses." International Journal of Biostatistics 12, no. 1 (2016): 45–63. http://dx.doi.org/10.1515/ijb-2015-0032.

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AbstractThe identification of patient subgroups with differential treatment effects is the first step towards individualised treatments. A current draft guideline by the EMA discusses potentials and problems in subgroup analyses and formulated challenges to the development of appropriate statistical procedures for the data-driven identification of patient subgroups. We introduce model-based recursive partitioning as a procedure for the automated detection of patient subgroups that are identifiable by predictive factors. The method starts with a model for the overall treatment effect as defined
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Wu, Wenhan, Wenfeng Yi, Jinghai Li, Maoyin Chen, and Xiaoping Zheng. "Automatic Identification of Human Subgroups in Time-Dependent Pedestrian Flow Networks." IEEE Transactions on Multimedia 26 (March 29, 2023): 166–77. https://doi.org/10.1109/TMM.2023.3262975.

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The study of identifying human subgroups from videos is a significant topic, which has received a lot of attention in multiple disciplines. So far, however, there has been little consideration about combining it with relevant conceptions in network science. Therefore, this article proposes a novel method for the automatic identification of human subgroups in dynamic pedestrian flows. The spatial proximity and temporal continuity are combined to calculate the interaction intensity between pedestrians, by which a time-dependent pedestrian flow network is constructed. Based on the objective funct
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Alagiozoglou, Lee, Freddy Sitas, and Lynn Morris. "Phylogenetic analysis of human herpesvirus-8 in South Africa and identification of a novel subgroup." Journal of General Virology 81, no. 8 (2000): 2029–38. http://dx.doi.org/10.1099/0022-1317-81-8-2029.

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The incidence of Kaposi’s sarcoma in South Africa is increasing in parallel with the human immunodeficiency virus type 1 epidemic. An 804 bp region in the ORF75 gene of 40 human herpesvirus-8 (HHV-8) isolates from South Africa was sequenced and the phylogenetic relationships were compared to published sequences. Nineteen strains clustered with subgroup B and 11 with subgroup A; however, the bootstrap values supporting these subgroups were not significant. Three strains grouped significantly with the C subgroup, while eight sequences did not cluster with any of the previously classified subgrou
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Ataei, Mohammad Javad. "Identification some groups with special subgroups." International Journal of Algebra 12, no. 3 (2018): 109–14. http://dx.doi.org/10.12988/ija.2018.71050.

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Lötsch, Jörn, and Alfred Ultsch. "Current Projection Methods-Induced Biases at Subgroup Detection for Machine-Learning Based Data-Analysis of Biomedical Data." International Journal of Molecular Sciences 21, no. 1 (2019): 79. http://dx.doi.org/10.3390/ijms21010079.

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Advances in flow cytometry enable the acquisition of large and high-dimensional data sets per patient. Novel computational techniques allow the visualization of structures in these data and, finally, the identification of relevant subgroups. Correct data visualizations and projections from the high-dimensional space to the visualization plane require the correct representation of the structures in the data. This work shows that frequently used techniques are unreliable in this respect. One of the most important methods for data projection in this area is the t-distributed stochastic neighbor e
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Martinovic, Borja, Jolanda Jetten, Anouk Smeekes, and Maykel Verkuyten. "Collective memory of a dissolved country: Group-based nostalgia and guilt assignment as predictors of interethnic relations between diaspora groups from former Yugoslavia." Journal of Social and Political Psychology 5, no. 2 (2018): 588–607. http://dx.doi.org/10.5964/jspp.v5i2.733.

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In this study we examined intergroup relations between immigrants of different ethnic backgrounds (Croats, Serbs, and Bosniaks) originating from the same conflict area (former Yugoslavia) and living in the same host country (Australia). For these (formerly) conflicted groups we investigated whether interethnic contacts depended on superordinate Yugoslavian and subgroup ethnic identifications as well as two emotionally laden representations of history: Yugonostalgia (longing for Yugoslavia from the past) and collective guilt assignment for the past wrongdoings. Using unique survey data collecte
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Dissertations / Theses on the topic "Subgroups Identification"

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Nesci, Julian, and julian nesci@gmail com. "Identification and clinical utility of subgroups of borderline personality disorder." RMIT University. Health Science, 2009. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20091022.141342.

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Borderline personality disorder (BPD) is a complex psychiatric condition whose severity is compounded by the heterogeneous psychological functioning of those who suffer from the disorder. This heterogeneity has made the identification of a unified treatment strategy difficult and attempts to resolve this variation within the disorder by investigating subtypes of BPD have been made. However, the clinical utility of this approach has not been examined. The major object of this research project was to investigate the presence of subtypes of BPD and to examine whether treatment effectiveness varie
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Raak, Ragnhild. "Identification of subgroups in experimental and chronic pain : sensory, emotional and evaluative aspects /." Linköping : Univ, 2002. http://www.bibl.liu.se/liupubl/disp/disp2002/med714s.pdf.

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Brode, Cassie. "Identification of Latent Subgroups of Obese Adolescents Enrolled in a Healthy Weight Management Program." VCU Scholars Compass, 2012. http://scholarscompass.vcu.edu/etd/373.

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In obesity research, it is assumed that the population is homogeneous. While this approach has yielded important insights, testing this supposition might reveal information that could impact our understanding of the phenomena and its treatment. In this study, data from obese teenagers (N = 248, Mean BMI percentile = 99%; Mean age = 13.9, SD = 1.8) who were predominantly minority (n = 182), female (n = 169), and enrolled in a weight loss intervention were analyzed. Latent profile analysis (LPA) was used to segment patients into groups based on their scores on PedsQL 4.0 scales (physical-, emoti
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Mo, Daojun. "The identification of subgroups of the general population susceptible to the effects of ambient particulate air pollution." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape9/PQDD_0019/MQ55079.pdf.

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Vendramini, E. "Identification of new subgroups and prognostic markers in pediatric B cell precursor acute lymphoblastic leukemia by gene expression profiling." Doctoral thesis, Università degli studi di Padova, 2010. http://hdl.handle.net/11577/3423224.

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Treatment of pediatric acute lymphoblastic leukemia (ALL) is increasingly successful, achieving cure rates of over 80%. Early identification of patients with high risk for relapse has led to improved outcome, however, two third of patients encountering relapse were initially stratified into low-intermediate risk groups. The identification of better upfront prognostic factors remains an important challenge in childhood ALL. In this thesis, gene expression profiling (GEP) was applied to different research approaches aiming to dissect subgroups and to find novel therapeutic targets in B cell pre
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Keller, Daniel L. "The identification and validation of teaching skills critical to generic elementary classroom teaching as determined by expert consensus among educator subgroups /." The Ohio State University, 1993. http://rave.ohiolink.edu/etdc/view?acc_num=osu14878480784499.

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Ivanauskas, Algirdas, and ALGIRDAS IVANAUSKAS. "Fitoplazmos ir jų vabzdžiai pernešėjai Lietuvoje." Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2014. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2014~D_20140620_091440-40989.

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Disertacijos darbo tikslas – aptikti ir identifikuoti Lietuvoje paplitusias fitoplazmas vabzdžiuose, surinktuose nuo įvairių augalų su fitoplazminiais simptomais ir nustatyti fitoplazmų vabzdžius pernešėjus bei atskleisti identifikuotų ir kitų fitoplazmų filogenetinius giminingumus. Lietuvoje jau žinomos keletas labiausiai paplitusių fitoplazmų grupių bei pogrupių, taip pat aptikta nemažai jų augalų-šeimininkų. Duomenų apie galimus šių bakterijų pernešėjus Lietuvoje beveik nėra. Pernešėjų identifikavimas ir tyrimas padės kurti veiksmingesnes strategijas bei sistemas kovai su fitoplazminėmis i
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Ivanauskas, Algirdas, and ALGIRDAS IVANAUSKAS. "Phytoplasmas and their insect vectors in Lithuania." Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2014. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2014~D_20140620_091456-96241.

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The aim of the research was to identify the phytoplasmas detected in insects that were found on various phytoplasma-infected plants, and to reveal phytoplasma insect-vectors as well as phytogenetical relationships of identified phytoplasmas. From previous research, we already know a few mostly widespread phytoplasma groups, subgroups, and many of their host plants in Lithuania. The data on potential vectors of these bacteria are very scarce in Lithuania. The identification and research of insect vectors will help to create more effective strategies and systems to fight with phytoplasmal infe
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PASTOR, ELIANA. "Pattern-based algorithms for Explainable AI." Doctoral thesis, Politecnico di Torino, 2021. http://hdl.handle.net/11583/2942116.

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Plata, Santos Hector Andres. "Subgroup identification in classification scenario with multiple treatments." Thesis, Linköpings universitet, Statistik och maskininlärning, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-166064.

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The subgroup identification field which sometimes is called personalized medicine, tries to group individuals such that the effects of a treatment are the most beneficial for them. One of the methods developed for this purpose is called PSICA. Currently this method works in a setting of multiple treatments and real valued response variables. In this thesis, this methodology is extended to the degree that it can also handle ordinal response variables that can take a finite number of values. It is also compared to a competitor method which results in similar performance but with the added value
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Books on the topic "Subgroups Identification"

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Kokin, Andrey, I. V. Latyshov, and P. Giverc. The current state and problems of identification in forensic ballistics. INFRA-M Academic Publishing LLC., 2022. http://dx.doi.org/10.12737/1873043.

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The monograph presents the modern concept of identification of firearms. The processes of weapons production necessitated adjustments to the traditional foundations of forensic ballistic identification, and a third group, subclass (subgroup) signs, is included in the binary system of general and particular signs of traces. An analysis of the modern practice of identifying firearms shows that the main obstacles in this process are subclass characteristics and prejudice. The first are related to the manufacture of parts and parts of weapons, and prejudice is associated with the subjective interp
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Superordinate identification, subgroup identification, and justice concerns: Is seperatism the problem, is assimilation the answer? American Bar Foundation, 1994.

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Kölker, Stefan. Glutaric Aciduria Type I. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199972135.003.0021.

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Glutaric aciduria type I is a rare organic aciduria caused by inherited deficiency of glutaryl-CoA dehydrogenase, a mitochondrial enzyme involved in the final common catabolic pathways of L-lysine, L-hydroxylysine, and L-trytophan. The majority of untreated patients develop striatal injury and secondary dystonia during infancy and childhood, whereas identification by newborn screening and immediate start of metabolic treatment (low-lysine diet, carnitine supplementation, metabolic emergency treatment) helps to prevent severe neurological complications in the majority of patients. The morbidity
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Book chapters on the topic "Subgroups Identification"

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Boylan, Kristin L. M., Keith M. Skubitz, and Amy P. N. Skubitz. "Subgroups of Ovarian Carinoma: Identification Using Differential Gene Expression." In Methods of Cancer Diagnosis, Therapy, and Prognosis. Springer Netherlands, 2009. http://dx.doi.org/10.1007/978-90-481-2918-8_4.

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Becker, James T. "Identification of Neuropsychologically Defined Subgroups of Alzheimer’s Disease Patients." In Critical Issues in Neuropsychology. Springer US, 1994. http://dx.doi.org/10.1007/978-1-4899-1196-4_8.

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Sathiyakumari, K., and M. S. Vijaya. "Identification of Subgroups in a Directed Social Network Using Edge Betweenness and Random Walks." In Smart Computing and Informatics. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-5544-7_12.

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Sidulova, Mariia, Xudong Sun, and Alexej Gossmann. "Deep Unsupervised Clustering for Conditional Identification of Subgroups Within a Digital Pathology Image Set." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-43993-3_64.

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Shen, Lei, Ying Ding, and Chakib Battioui. "A Framework of Statistical Methods for Identification of Subgroups with Differential Treatment Effects in Randomized Trials." In ICSA Book Series in Statistics. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-12694-4_25.

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Hernandez, Céline, Gabriele Cancila, Olivier Ayrault, Andrei Zinovyev, and Loredana Martignetti. "ClustMMRA v2: A Scalable Computational Pipeline for the Identification of MicroRNA Clusters Acting Cooperatively on Tumor Molecular Subgroups." In Advances in Experimental Medicine and Biology. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08356-3_10.

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Brossollet, Ivan, Quentin Gallet, Pauline Favre, and Josselin Houenou. "Machine Learning and Brain Imaging for Psychiatric Disorders: New Perspectives." In Machine Learning for Brain Disorders. Springer US, 2023. http://dx.doi.org/10.1007/978-1-0716-3195-9_32.

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AbstractPsychiatric disorders include a broad panel of heterogeneous conditions. Among the most severe psychiatric diseases, in intensity and incidence, depression will affect 15–20% of the population in their lifetime, schizophrenia 0.7–1%, and bipolar disorder 1–2.5%. Today, the diagnosis is solely based on clinical evaluation, causing major issues since it is subjective and as different diseases can present similar symptoms. These limitations in diagnosis lead to limitations in the classification of psychiatric diseases and treatments. There is therefore a great need for new biomarkers, usa
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Huang, Xin, Yihua Gu, Yan Sun, and Ivan S. F. Chan. "Exploratory Subgroup Identification for Biopharmaceutical Development." In Emerging Topics in Statistics and Biostatistics. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-40105-4_12.

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Loh, Wei-Yin, and Peigen Zhou. "The GUIDE Approach to Subgroup Identification." In Emerging Topics in Statistics and Biostatistics. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-40105-4_6.

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Man, M., T. S. Nguyen, C. Battioui, and G. Mi. "Predictive Subgroup/Biomarker Identification and Machine Learning Methods." In Statistical Methods in Biomarker and Early Clinical Development. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31503-0_1.

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Conference papers on the topic "Subgroups Identification"

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Kuratomi, Alejandro, Zed Lee, Panayiotis Tsaparas, et al. "CounterFair: Group Counterfactuals for Bias Detection, Mitigation and Subgroup Identification." In 2024 IEEE International Conference on Data Mining (ICDM). IEEE, 2024. https://doi.org/10.1109/icdm59182.2024.00025.

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Gieg, Lisa, Mohita Sharma, Jennifer Sargent, et al. "Synergistic Effect of Biocide and Biodispersant to Mitigate Microbiologically Influenced Corrosion in Crude Oil Transmission Pipelines." In CORROSION 2020. NACE International, 2020. https://doi.org/10.5006/c2020-15090.

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Abstract Crude oil transmission pipelines are treated with chemicals to mitigate microbiologically influenced corrosion (MIC). Often such corrosion occurs at over and under bends in pipelines due to the flow regimes that allow the suspended particulate in the crude to settle. The resulting sludge, typically composed of oil, water, and sand, can be microbiologically active. For testing, sludge is collected from the nose of a cleaning pig, but the locations of sample collection are frequently remote. As such, onsite testing of the sludge can be impractical, thus samples usually travel long dista
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Prananpaeng, Sutthiphan, Thiradon Thaiyanto, Ratsameetip Wita, and Nampeung Anukul. "Whole-Exome Sequencing (WES) Analysis for ABO Subgroups Identification." In 2023 20th International Joint Conference on Computer Science and Software Engineering (JCSSE). IEEE, 2023. http://dx.doi.org/10.1109/jcsse58229.2023.10202117.

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Metzen, Jan Hendrik, Robin Hutmacher, N. Grace Hua, Valentyn Boreiko, and Dan Zhang. "Identification of Systematic Errors of Image Classifiers on Rare Subgroups." In 2023 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE, 2023. http://dx.doi.org/10.1109/iccv51070.2023.00467.

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Akoglu, Leman, Hanghang Tong, Brendan Meeder, and Christos Faloutsos. "PICS: Parameter-free Identification of Cohesive Subgroups in Large Attributed Graphs." In Proceedings of the 2012 SIAM International Conference on Data Mining. Society for Industrial and Applied Mathematics, 2012. http://dx.doi.org/10.1137/1.9781611972825.38.

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Gala, Kinisha, Darko Medin, Ankit Kalucha, Judith Pérez Granado, Bruno Larvol, and Mark Gramling. "903 Identification of non-small cell lung cancer (NSCLC) patient subgroups with poor response to immunotherapy using subgroup-level meta-analyses." In SITC 38th Annual Meeting (SITC 2023) Abstracts. BMJ Publishing Group Ltd, 2023. http://dx.doi.org/10.1136/jitc-2023-sitc2023.0903.

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Kar, Subhajit, Kaushik Das Sharma, and Madhubanti Maitra. "A particle swarm optimization based gene identification technique for classification of cancer subgroups." In 2016 2nd International Conference on Control, Instrumentation, Energy & Communication (CIEC). IEEE, 2016. http://dx.doi.org/10.1109/ciec.2016.7513800.

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Zhu, Huiyi, Chanyuan Wu, Nan Jiang, et al. "OP0062 IDENTIFICATION OF SIX DERMATOMYOSITIS SUBGROUPS USING PRINCIPAL COMPONENT ANALYSIS-BASED CLUSTER ANALYSIS." In Annual European Congress of Rheumatology, EULAR 2019, Madrid, 12–15 June 2019. BMJ Publishing Group Ltd and European League Against Rheumatism, 2019. http://dx.doi.org/10.1136/annrheumdis-2019-eular.385.

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Gianfrancesco, Milena A., Benjamin S. Glicksberg, Andy Dahl, et al. "58 Identification of systemic lupus erythematosus subgroups using electronic health record and genetic databases." In 13th International Congress on Systemic Lupus Erythematosus (LUPUS 2019), San Francisco, California, USA, April 5–8, 2019, Abstract Presentations. Lupus Foundation of America, 2019. http://dx.doi.org/10.1136/lupus-2019-lsm.58.

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Xu, Tianfu, Xueyun Hu, Caifeng Zhu, and Chenggong He. "Identification of molecular subgroups in major depressive disorder based on the gene expression profiles." In 2022 16th ICME International Conference on Complex Medical Engineering (CME). IEEE, 2022. http://dx.doi.org/10.1109/cme55444.2022.10063296.

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Reports on the topic "Subgroups Identification"

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El-Bakry, A. S., R. A. Tapia, and Y. Zhang. Logarithmic Indicators and the Identification of Subgroups of Variables in Interior-Point Methods. Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/ada444980.

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Li, Sheyu, Valentyn Litvin, and Charles Manski. Partial Identification of Personalized Treatment Response with Trial-reported Analyses of Binary Subgroups. National Bureau of Economic Research, 2022. http://dx.doi.org/10.3386/w30461.

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Székely, Miguel. Policy Options for Poverty Alleviation. Inter-American Development Bank, 1997. http://dx.doi.org/10.18235/0010754.

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This work builds on previous research to develop a methodology that simplifies the identification of the best policy options for poverty alleviation in a given country. When a population can be divided into subgroups according to an easily identifiable characteristic, the problem of alleviating poverty through a targeted mechanism can be viewed as one of choosing of three options: (i) provoking a marginal change in the average income of certain subgroups; (ii) changing the resource distribution within marginal subgroups; and (iii) generating a marginal change in the differences between the sub
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Wu, Ling, Tao Zhang, Yao Wang, et al. Polymorphisms and premature ovarian insufficiency and failure: A comprehensive meta-analysis update, subgroup, ranking, and network analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2022. http://dx.doi.org/10.37766/inplasy2022.1.0052.

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Review question / Objective: Early identification of women potentially who develop POI and POF is essential for early screening and treatment to improve clinical outcomes. We aim to conduct a comprehensive meta-analysis update, subgroup, ranking and network analysis for all available genetic polymorphism and associated with the POI and POF risk. Information sources: Six electronic databases will be included such as PubMed, Web of Science, Embase, MEDLINE, WANFANG DATA, CNKI. Will contact with authors by emails when necessary.
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Botulinum Neurotoxin-Producing Clostridia, Working Group on. Report on Botulinum Neurotoxin-Producing Clostridia. Food Standards Agency, 2023. http://dx.doi.org/10.46756/sci.fsa.ozk974.

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In 1992 a working group of the UK Advisory Committee on the Microbiological Safety of Food presented a report on Vacuum Packaging and Associated Processes regarding the microbiological safety of chilled foods. The report supported subsequent guidance provided by the UK Food Standards Agency for the safe manufacture of vacuum packed and modified atmosphere packed chilled foods. In 2021 the ACMSF requested that a new subgroup should update and build on the 1992 report as well as considering, in addition to chilled foods, some foods that are intended to be stored at ambient temperatures. The new
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Haynes, Ben, Tahmnina Khan, Ruth Willis, Camilla Alexander-White, and Alan Boobis. Joint position paper from the Advisory Committee on Novel Foods and Processes (ACNFP) & Committee on Toxicity (COT) on establishing a provisional acceptable daily intake (ADI) for pure form (≥98%) cannabidiol (CBD) in foods, based on new evidence. Food Standards Agency, 2023. http://dx.doi.org/10.46756/sci.fsa.zcg392.

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Following the announcement by the FSA that from 31st March 2021, all CBD products on the market must have their safety assured by companies submitting a valid safety application, there have been a large number of CBD-related novel food applications. Consequently, a significant level of additional data has become available that requires review. A joint Subgroup of the ACNFP and COT was formed to address a series of questions in relation to the safety of CBD-containing and hemp-derived ingredients. The overarching aim of the Subgroup is to enable the FSA to perform risk assessments for CBD in fo
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