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Gotowe bibliografie tematyczne / Severity heatmap

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Gotowa bibliografia na temat „Severity heatmap”

Autor: Grafiati

Data publikacji: 2 czerwca 2025

Data aktualizacji: 31 lipca 2025

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Artykuły w czasopismach na temat "Severity heatmap"

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Ma, Yingying, Xiaoran Qin, Offer Grembek, and Zhiwei Chen. "Developing a safety heatmap of uncontrolled intersections using both conflict probability and severity." Accident Analysis & Prevention 113 (April 2018): 303–16. http://dx.doi.org/10.1016/j.aap.2018.01.038.

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Van der Cruyssen, Frederic, Mathilda Wylde, Anthony Campbell, et al. "Quantitative and Qualitative Symmetry Analysis of Open Reduction and Fixation of Zygomatic Complex Fractures." Craniomaxillofacial Trauma & Reconstruction 18, no. 2 (2025): 22. https://doi.org/10.3390/cmtr18020022.

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Zygomatic complex (ZMC) fractures are among the most common craniofacial injuries, impacting both function and esthetics. This study evaluates the effectiveness of open reduction and internal fixation (ORIF) in restoring facial symmetry following ZMC fractures. Sixteen patients with unilateral ZMC fractures underwent a retrospective analysis comparing preoperative and postoperative computed tomography (CT) scans to a control group of ten individuals without facial fractures. Quantitative metrics, including root mean square distance (RMSD) and heatmap analysis, were used alongside a qualitative

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Espinosa, Luis Angel, and Maria Manuela Portela. "Red-Hot Portugal: Mapping the Increasing Severity of Exceptional Maximum Temperature Events (1980–2024)." Atmosphere 16, no. 5 (2025): 514. https://doi.org/10.3390/atmos16050514.

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This study examines exceptional maximum temperature (Tmax) events in mainland Portugal (1980–2024) using ERA5-Land reanalysis data at 1012 locations. To assess changes in the occurrence and temperature excess of exceptional events across two 22-year subperiods (or phases), percentile-based thresholds were adopted. An inventive severity heatmap is used to illustrate exceptional Tmax changes between the two phases, which constitutes an addition to climate change research. Locations are categorised in the heatmap according to whether they experienced (i) more occurrences and more temperature exce

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Silva, Julio Cezar Soares, Nivan Roberto Ferreira, and Adiel Teixeira de Almeida Filho. "A Tool for Visualization and Analysis of Neighbourhoods, Clusters, and Indicators during the COVID-19 Pandemic." Mathematical Problems in Engineering 2023 (February 20, 2023): 1–16. http://dx.doi.org/10.1155/2023/9524753.

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Visual analytics tools for spatiotemporal analysis can be used to manage and monitor the propagation of an epidemic. The problem is that dashboards encountered in the literature do not take into consideration how the geolocation characteristics, such as socioeconomic indicators, influence the infection risk or other epidemic variables. This analysis can support health officials in managing the outbreak to consider information about indicators in compartment models for propagation prediction and intervention simulation. The objective of this work was to bring widgets that offer a more profound

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Umebayashi, Ryoko, Haruhito Adam Uchida, Natsumi Matsuoka-Uchiyama, Hitoshi Sugiyama, and Jun Wada. "Prevalence of Chronic Kidney Disease and Variation of Its Risk Factors by the Regions in Okayama Prefecture." Journal of Personalized Medicine 12, no. 1 (2022): 97. http://dx.doi.org/10.3390/jpm12010097.

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Objective: The prevention of chronic kidney disease (CKD) progression is an important issue from health and financial perspectives. We conducted a single-year cross-sectional study to clarify the prevalence of CKD and its risk factors along with variations in these factors among five medical regions in Okayama Prefecture, Japan. Methods and Results: Data concerning the renal function and proteinuria as well as other CKD risk factors were obtained from the database of the Japanese National Health Insurance. The proportion of CKD patients at an increased risk of progression to end-stage renal di

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Filippis, Rocco de, and Abdullah Al Foysal. "Predictive Analysis of Neuroleptics-Induced Obsessive-Compulsive Symptoms Using Machine Learning." Journal of Mathematical Techniques and Computational Mathematics 3, no. 8 (2024): 01–07. https://doi.org/10.33140/jmtcm.03.08.008.

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Background Neuroleptics, or antipsychotic medications, are widely used in the treatment of various psychiatric disorders. However, they have been associated with the secondary development of obsessive-compulsive symptoms (OCS) in some patients. This case report examines two patients who developed obsessive-compulsive aspects secondary to neuroleptic treatment. Objective To evaluate the development of OCS in patients treated with neuroleptics and to analyse their clinical outcomes. Methods Two patients treated with neuroleptics were assessed for the emergence of obsessive-compulsive symptoms us

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Filippis, Rocco de, and Abdullah Al Foysal. "Predictive Analysis of Neuroleptics-Induced Obsessive-Compulsive Symptoms Using Machine Learning." Journal of Mathematical Techniques and Computational Mathematics 3, no. 8 (2024): 01–07. http://dx.doi.org/10.33140/jmtcm.03.08.08.

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Background Neuroleptics, or antipsychotic medications, are widely used in the treatment of various psychiatric disorders. However, they have been associated with the secondary development of obsessive-compulsive symptoms (OCS) in some patients. This case report examines two patients who developed obsessive-compulsive aspects secondary to neuroleptic treatment. Objective To evaluate the development of OCS in patients treated with neuroleptics and to analyse their clinical outcomes. Methods Two patients treated with neuroleptics were assessed for the emergence of obsessive-compulsive symptoms us

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Schepens, Emma J. A., Digna M. A. Kamalski, and Inge Stegeman. "A Comparative Analysis of the Incidence, Severity and Duration of Smell and Taste Loss in COVID-19 Cases Versus Non-COVID-19 Cases: A Longitudinal Cohort Study." Journal of Clinical Medicine 12, no. 19 (2023): 6267. http://dx.doi.org/10.3390/jcm12196267.

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The COVID-19 pandemic has highlighted the relevance of olfactory and gustatory disorders. However, these symptoms can also be caused by various other factors. In this study we aimed to compare the incidence, severity and duration between COVID-19 related and non-COVID-19 related smell and taste disorders. We conducted a longitudinal cohort study using data from the Dutch biobank Lifelines, which includes over 167,000 participants. The data were collected using 27 questionnaires distributed between March 2020 and May 2022. Descriptive data and the incidence of smell and taste loss in both group

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Priyanka, K., A. V. Narendran, S. B. Shanjaiy, M. Sivanesh, A. Vasanthbalan, and G. Yokesh. "Secure Coding Analysis Tool." Research and Reviews: Advancement in Cyber Security 2, no. 3 (2025): 46–52. https://doi.org/10.5281/zenodo.15583548.

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<em>Secure Code Analysis Tool is an extensive project that makes it easy and automatic to identify security vulnerabilities in software codebases. It is meant to make it easy to identify, explain, and report potential security threats in web, mobile, and API apps. It scans source code to identify typical security vulnerabilities like injection attacks, unsafe data management, and misconfigurations. It then produces human-friendly descriptions for the developers, enabling them to easily comprehend the type of vulnerabilities. The system also provides severity ratings and plots vulnerability dis

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Filippova, Yu Yu, E. V. Devyatova, A. S. Alekseeva, and A. L. Burmistrova. "Cytokines and neurotrophic factors in the severity assessment of children autism." Russian Clinical Laboratory Diagnostics 67, no. 11 (2022): 647–51. http://dx.doi.org/10.51620/0869-2084-2022-67-11-647-651.

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Due to the steady increase in the number of children with autism and the high heterogeneity of clinical groups, the diagnosis of these disorders and their severity is an urgent problem in modern medicine. In the course of the work, 126 children from 3 to 13 years old with typical neurodevelopment and with severe and mild autism spectrum disorders (ASD) were examined. Disease severity was determined according to the Childhood Autism Rating Scale (CARS). The levels of pro-/anti-inflammatory cytokines and neurotrophic factors (nerve growth factor beta and brain-derived neurotrophic factor) in blo

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Streszczenia konferencji na temat "Severity heatmap"

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Silva, Charith, and Mo Saraee. "Predicting Road Traffic Accident Severity using Decision Trees and Time-Series Calendar Heatmaps." In 2019 IEEE Conference on Sustainable Utilization and Development in Engineering and Technologies (CSUDET). IEEE, 2019. http://dx.doi.org/10.1109/csudet47057.2019.9214709.

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Yahia, Hana, Thomas Romary, Laurent Gerbaud, Stephane Menand, and Mohamed Mahjoub. "Real-Time Stick-Slip Mitigation Using Combined Machine Learning and Physics Based Techniques." In International Petroleum Technology Conference. IPTC, 2024. http://dx.doi.org/10.2523/iptc-24509-ms.

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Abstract Downhole vibrations can lead to significant drilling problems in unconventional wells, such as frequent tool failures that increase drilling costs. Detecting these vibrations during drilling is crucial for enhancing drilling practices. One of the most destructive types of downhole vibrations is torsional stick-slip, characterized by fluctuations in bit rotation speed between zero and several times the surface rotation speed. Typically, surface data is used for real-time diagnosis of this drilling dysfunction. In recent years, Artificial Intelligence (AI)-based detection algorithms hav

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Ade-olusile, Binta, Zainb Dawod, and Saeed Sharif. "Early Detection of Arthritis Using Convolutional Neural Networks and Explainable AI." In Human Interaction and Emerging Technologies (IHIET-FS 2025): Future Systems and Artificial Intelligence Applications. AHFE International, 2025. https://doi.org/10.54941/ahfe1005960.

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Arthritis is a prevalent and debilitating musculoskeletal disorder that significantly impairs mobility, joint function, and overall quality of life for millions of individuals across the globe. The condition is characterized by chronic joint inflammation, cartilage degradation, stiffness, and persistent pain, often leading to long-term disability and increased healthcare dependency. As the global population continues to age, the healthcare impact and economic burden of arthritis are expected to rise substantially. Early detection and precise classification of arthritis are therefore essential

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Ade-olusile, Binta, Zainb Dawod, and Saeed Sharif. "Early Detection of Arthritis Using Convolutional Neural Networks and Explainable AI." In Human Interaction and Emerging Technologies (IHIET-FS 2025): Future Systems and Artificial Intelligence Applications. AHFE International, 2025. https://doi.org/10.54941/ahfe10059725960.

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Arthritis is a prevalent and debilitating musculoskeletal disorder that significantly impairs mobility, joint function, and overall quality of life for millions of individuals across the globe. The condition is characterized by chronic joint inflammation, cartilage degradation, stiffness, and persistent pain, often leading to long-term disability and increased healthcare dependency. As the global population continues to age, the healthcare impact and economic burden of arthritis are expected to rise substantially. Early detection and precise classification of arthritis are therefore essential

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Tariq, Zeeshan, Muhammad Ali, Bicheng Yan, et al. "Data-Driven Machine Learning Modeling of Mineral/CO2/Brine Wettability Prediction: Implications for CO2 Geo-Storage." In Middle East Oil, Gas and Geosciences Show. SPE, 2023. http://dx.doi.org/10.2118/213346-ms.

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Abstract CO2 wettability and the reservoir rock-fluid interfacial interactions are crucial parameters for successful CO2 geological sequestration. This study implemented the feed-forward neural network to model the wettability behavior in a ternary system of rock minerals (quartz and mica), CO2, and brine under different operating conditions. To gain higher accuracy of the machine learning models, a sufficient dataset was utilized that was recorded by conducting a large number of laboratory experiments under a realistic pressure range, 0 – 25 MPa and the temperatures range, 298 – 343 K. The mi

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