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检索条件"机构=Informatics and Data Science Program"
285 条 记 录,以下是11-20 订阅
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Multimodal AI predicts clinical outcomes of drug combinations from preclinical data
arXiv
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arXiv 2025年
作者: Huang, Yepeng Su, Xiaorui Ullanat, Varun Liang, Ivy Clegg, Lindsay Olabode, Damilola Ho, Nicholas John, Bino Gibbs, Megan Zitnik, Marinka Department of Biomedical Informatics Harvard Medical School BostonMA United States Program in Biological and Biomedical Sciences Harvard Medical School BostonMA United States Harvard College CambridgeMA United States Clinical Pharmacology and Quantitative Pharmacology Clinical Pharmacology & Safety Sciences R&D AstraZeneca GaithersburgMD United States Clinical Pharmacology and Quantitative Pharmacology Clinical Pharmacology & Safety Sciences R&D AstraZeneca WalthamMA United States Program in Computational Biology Carnegie Mellon University PittsburghPA United States Imaging and Data Analytics Clinical Pharmacology & Safety Sciences R&D AstraZeneca WalthamMA United States Kempner Institute for the Study of Natural and Artificial Intelligence Harvard University AllstonMA United States Broad Institute of MIT and Harvard CambridgeMA United States Harvard Data Science Initiative CambridgeMA United States
Predicting clinical outcomes from preclinical data is essential for identifying safe and effective drug combinations, reducing late-stage clinical failures, and accelerating the development of precision therapies. Cur... 详细信息
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On the combination of two visual cognition systems using combinatorial fusion
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Brain informatics 2015年 第1期2卷 21-32页
作者: Batallones, Amy Sanchez, Kilby Mott, Brian Coffran, Cameron Frank Hsu, D. Laboratory of Informatics and Data Mining Department of Computer and Information Science Fordham University New YorkNY United States Program for the Human Environment The Rockefeller University New YorkNY United States
When combining decisions made by two separate visual cognition systems, statistical means such as simple average (M1) and weighted average (M2 and M3), incorporating the confidence level of each of these systems have ... 详细信息
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Mapping Emergency Medicine data to the Observational Medical Outcomes Partnership Common data Model: A Gap Analysis of the American College of Emergency Physicians Clinical Emergency data Registry
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JACEP Open 2025年 第1期6卷 100016-100016页
作者: Cohen, Inessa Diao, Zihan Goyal, Pawan Gupta, Aarti Hawk, Kathryn Malcom, Bill Malicki, Caitlin Sharma, Dhruv Sweeney, Brian Weiner, Scott G. Venkatesh, Arjun Taylor, R. Andrew Department of Emergency Medicine Yale School of Medicine New Haven CT United States Section for Biomedical Informatics and Data Science Yale University School of Medicine New Haven CT United States Program of Computational Biology and Bioinformatics Yale University New Haven CT United States American College of Emergency Physicians Washington DC United States Department of Emergency Medicine Brigham and Women's Hospital Boston MA United States Center for Outcomes Research and Evaluation (CORE) Section of Cardiovascular Medicine Yale School of Medicine New Haven CT United States
Objectives: This study aims to conduct a gap analysis to determine the feasibility of mapping electronic health record data from the Clinical Emergency data Registry (CEDR) to the Observational Medical Outcomes Partne... 详细信息
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Sex differences in proteomics of cardiovascular disease – Results from the Yale-CMD registry
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IJC Heart and Vasculature 2025年 58卷 101667-101667页
作者: Liu, Yihan Wang, Zuoheng Collins, Sean P. Testani, Jeffery Safdar, Basmah Program in Computational Biology & Biomedical informatics Yale University New Haven CT United States Department of Biostatistics Yale University School of Public Health New Haven CT United States Department of Biomedical Informatics & Data Science Yale University School of Medicine New Haven CT United States Department of Emergency Medicine Vanderbilt University Medical Center Veterans Affairs Tennessee Valley Healthcare System Geriatric Research Education and Clinical Center (GRECC) Nashville TN United States Section of Cardiovascular Medicine Department of Internal Medicine Yale University School of Medicine New Haven CT United States Department of Emergency Medicine Yale University School of Medicine New Haven CT United States
Aims This study assessed sex-specific proteomic profiles by cardiovascular disease (CVD) phenotype (coronary artery disease [CAD] vs coronary microvascular dysfunction [CMD]) and describe their role in sex-specific pa... 详细信息
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Uncertainty abounds, what now?
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science 2025年 第6740期387卷 1261页
作者: Dov Greenbaum Mark Gerstein The reviewer is at the Zvi Meitar Institute for Legal Implications of Emerging Technologies The reviewer is at the Harry Radzyner Law School The reviewer is at the Dina Recanati School of Medicine Reichman University Herzliya Israel The reviewer is at the Department of Biomedical Informatics and Data Science The reviewer is at the Program in Computational Biology and Bioinformatics The reviewer is at the Department of Computer Science Yale University New Haven CT USA.
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Machine Learning and Deep Learning Techniques for Prediction and Diagnosis of Leptospirosis: Systematic Literature Review
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JMIR Medical informatics 2025年 13卷 e67859页
作者: Suhila Sawesi Arya Jadhav Bushra Rashrash Health Informatics and Bioinformatics Program College Of Computing Grand Valley State University 333 Michigan St. NE Grand Rapids MI United States Data Science College Of Computing Grand Valley State University Allendale MI United States Department of Biomedical Science College of Liberal Arts and Sciences Grand Valley State University Allendale MI United States
Background Leptospirosis, a zoonotic disease caused by Leptospira bacteria, continues to pose significant public health risks, particularly in tropical and subtropical regions. Objective This systematic review aimed t... 详细信息
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The spatial zonation of the murine placental vasculature is specified by epigenetic mechanisms
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Developmental Cell 2025年 第10期60卷 1467-1482.e8页
作者: Gehrs, Stephanie Jakab, Moritz Gutjahr, Ewgenija Gu, Zuguang Weichenhan, Dieter Mallm, Jan-Philipp Mogler, Carolin Schlesner, Matthias Plass, Christoph Schlereth, Katharina Augustin, Hellmut G. Division of Vascular Oncology and Metastasis German Cancer Research Center (DKFZ) Heidelberg 69120 Germany European Center for Angioscience (ECAS) Medical Faculty Mannheim Heidelberg University Mannheim 68167 Germany Faculty of Biosciences Heidelberg University Heidelberg 69120 Germany Institute of Pathology University Clinic Heidelberg Heidelberg 69120 Germany Computational Oncology Group Molecular Precision Oncology Program National Center for Tumor Diseases (NCT) Heidelberg and German Cancer Research Center (DKFZ) Heidelberg 69120 Germany Division of Cancer Epigenomics German Cancer Research Center (DKFZ) Heidelberg 69120 Germany Division of Chromatin Networks German Cancer Research Center (DKFZ) and Bioquant Heidelberg 69120 Germany Institute of Pathology TUM School of Medicine Technical University of Munich Munich 80333 Germany Biomedical Informatics Data Mining and Data Analytics Faculty of Applied Computer Science and Medical Faculty University of Augsburg Augsburg 86159 Germany
The labyrinthian fetoplacental capillary network is vital for proper nourishment of the developing embryo. Dysfunction of the maternal-fetal circulation is a primary cause of placental insufficiency. Here, we show tha... 详细信息
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A Consensus Privacy Metrics Framework for Synthetic data
arXiv
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arXiv 2025年
作者: Pilgram, Lisa Dankar, Fida K. Drechsler, Jörg Elliot, Mark Domingo-Ferrer, Josep Francis, Paul Kantarcioglu, Murat Kong, Linglong Malin, Bradley Muralidhar, Krishnamurty Myles, Puja Prasser, Fabian Raisaro, Jean Louis Yan, Chao El Emam, Khaled School of Epidemiology and Public Health University of Ottawa ON Canada CHEO Research Institute ON Canada Department of Nephrology and Medical Intensive Care Charité – Universitätsmedizin Berlin Berlin Germany Department for Statistical Methods Institute for Employment Research Nuernberg Germany Institute for Statistics Ludwig-Maximilians-Universität Munich Germany Joint Program in Survey Methodology University of Maryland United States The Cathie Marsh Institute Research School of Social Sciences University of Manchester Manchester United Kingdom Department of Computer Engineering and Mathematics Universitat Rovira i Virgili Catalonia Tarragona Spain Max Planck Institute for Software Systems Germany Department of Computer Science Virginia Tech United States Department of Mathematical and Statistical Sciences University of Alberta Alberta Canada Department of Biomedical Informatics Vanderbilt University Medical Center NashvilleTN United States Department of Biostatistics Vanderbilt University Medical Center NashvilleTN United States Department of Computer Science Vanderbilt University NashvilleTN United States Department of Marketing and Supply Chain Management University of Oklahoma Oklahoma United States Medicines and Healthcare products Regulatory Agency London United Kingdom Berlin Institute of Health at Charité Universitätsmedizin Berlin Medical Informatics Group Berlin Germany Biomedical Data Science Center University Hospital Lausanne Lausanne Switzerland
Synthetic data generation is one approach for sharing individual-level data. However, to meet legislative requirements, it is necessary to demonstrate that the individuals’ privacy is adequately protected. There is n... 详细信息
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MedRep: Medical Concept Representation for General Electronic Health Record Foundation Models
arXiv
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arXiv 2025年
作者: Kim, Junmo Lee, Namkyeong Kim, Jiwon Kim, Kwangsoo Interdisciplinary Program in Bioengineering Seoul National University Korea Republic of Dept. of Industrial and Systems Engineering KAIST Korea Republic of Interdisciplinary Program of Medical Informatics Seoul National University Korea Republic of Dept. of Transdisciplinary Medicine ICMIT Seoul National University Hospital Korea Republic of Center for Data Science Healthcare AI Research Institute Seoul National University Hospital Korea Republic of Dept. of Medicine College of Medicine Seoul National University Korea Republic of
Electronic health record (EHR) foundation models have been an area ripe for exploration with their improved performance in various medical tasks. Despite the rapid advances, there exists a fundamental limitation: Proc... 详细信息
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ConvNeXt Model for Breast Cancer Image Classification  6
ConvNeXt Model for Breast Cancer Image Classification
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6th International Conference on Cybernetics and Intelligent System, ICORIS 2024
作者: Setiawan, Devin Karnyoto, Andrea Stevens Intan, Indo Pardamean, Bens Department of Electrical Engineering and Computer Science University of Kansas Lawrence United States Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Department of Informatics Engineering Universitas Dipa Makassar Makassar Indonesia Computer Science Department BINUS Graduate Program Computer Science Program Bina Nusantara University Jakarta Indonesia
Breast cancer is an occurrence of cancer that attacks breast tissue and is the most common cancer among women worldwide, affecting one in eight women. In this modern world, breast cancer image classification simplifie... 详细信息
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