Jeremy C Weiss

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	Wszystkie	Od 2020
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Wenbin ZhangFlorida International UniversityZweryfikowany adres z fiu.edu
Walid GelladUniversity of Pittsburgh, VA, RANDZweryfikowany adres z rand.org
Wei-Hsuan Jenny Lo-CiganicProfessor, Division of General Internal Medicine, University of PittsburghZweryfikowany adres z pitt.edu
Derek C AngusProfessor, University of PittsburghZweryfikowany adres z upmc.edu
Shyam VisweswaranProfessor of Biomedical Informatics, University of PittsburghZweryfikowany adres z pitt.edu
Sriraam NatarajanUniversity of Texas at DallasZweryfikowany adres z utdallas.edu
George H. ChenAssociate Professor, Carnegie Mellon UniversityZweryfikowany adres z cmu.edu
Peggy PeissigMarshfield Clinic Research InstituteZweryfikowany adres z marshfieldresearch.org
Juyong KimPhD student in Machine Learning Department, Carnegie Mellon UniversityZweryfikowany adres z andrew.cmu.edu
Pradeep RavikumarProfessor, School of Computer Science, Carnegie Mellon UniversityZweryfikowany adres z cs.cmu.edu
Cheng ChengPh.D. Student, Carnegie Mellon UniversityZweryfikowany adres z andrew.cmu.edu
Finn KuusistoUniversity of Wisconsin-MadisonZweryfikowany adres z cs.wisc.edu
Zachary C. LiptonRaj Reddy Associate Professor of Machine Learning @ Carnegie Mellon University; CTO + CSO @ AbridgeZweryfikowany adres z cmu.edu
Helen ZhouCarnegie Mellon UniversityZweryfikowany adres z andrew.cmu.edu
Kenneth RiceUniversity of WashingtonZweryfikowany adres z uw.edu
Gina Schellenbaum LovasiDrexel UniversityZweryfikowany adres z drexel.edu
David PageDuke UniversityZweryfikowany adres z duke.edu
Kendrick BoydUniversity of Wisconsin-MadisonZweryfikowany adres z cs.wisc.edu
Jie LiuUniversity of MichiganZweryfikowany adres z umich.edu
Xuejian WangPhD student in Machine Learning and Public Policy, Carnegie Mellon UniversityZweryfikowany adres z andrew.cmu.edu

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Jeremy C Weiss

Investigator, National Library of Medicine, National Institutes of Health

Zweryfikowany adres z nih.gov - Strona główna

Health Informatics Machine Learning


Tytuł Sortuj wg cytatów Sortuj wg roku Sortuj wg tytułu	Cytowane przez Cytowane przez	Rok
Derivation, Validation, and Potential Treatment Implications of Novel Clinical Phenotypes for Sepsis CW Seymour, JN Kennedy, S Wang, CCH Chang, CF Elliott, Z Xu, S Berry, ... Journal of the American Medical Association, 2019	1151	2019
Evaluation of Machine-Learning Algorithms for Predicting Opioid Overdose Risk Among Medicare Beneficiaries With Opioid Prescriptions PD Wei-Hsuan Lo-Ciganic, PD James L. Huang, PD Hao H. Zhang, ... JAMA Network Open, 2019	225	2019
Machine learning for personalized medicine: predicting primary myocardial infarction from electronic health records JC Weiss, S Natarajan, PL Peissig, CA McCarty, D Page AI Magazine 33 (4), 33-33, 2012	119	2012
Farf: A fair and adaptive random forests classifier W Zhang, A Bifet, X Zhang, JC Weiss, W Nejdl Pacific-Asia conference on knowledge discovery and data mining, 245-256, 2021	67	2021
Longitudinal fairness with censorship W Zhang, JC Weiss proceedings of the AAAI conference on artificial intelligence 36 (11), 12235 …, 2022	63	2022
An Open Repository of Real-Time COVID-19 Indicators A Reinhart, L Brooks, M Jahja, A Rumack, J Tang, W Al Saeed, T Arnold, ... Proceedings of the National Academy of Sciences 118 (51), 2021	63	2021
Forest-based point processes for event prediction from electronic health records JC Weiss, D Page Machine learning and knowledge discovery in databases, 547-562, 2013	61	2013
Fair decision-making under uncertainty W Zhang, JC Weiss 2021 IEEE international conference on data mining (ICDM), 886-895, 2021	52	2021
Comparing a single-stage geocoding method to a multi-stage geocoding method: how much and where do they disagree? GS Lovasi, JC Weiss, R Hoskins, EA Whitsel, K Rice, CF Erickson, ... International Journal of Health Geographics 6, 1-11, 2007	45	2007
Developing and validating a machine-learning algorithm to predict opioid overdose in Medicaid beneficiaries in two US states: a prognostic modelling study WH Lo-Ciganic, JM Donohue, Q Yang, JL Huang, CY Chang, JC Weiss, ... The Lancet Digital Health 4 (6), e455-e465, 2022	43	2022
Machine Learning for Treatment Assignment: Improving Individualized Risk Attribution JC Weiss, F Kuusisto, K Boyd, J Liu, CD Page American Medical Informatics Association Annual Symposium, 2015	43	2015
Using machine learning to predict risk of incident opioid use disorder among fee-for-service Medicare beneficiaries: A prognostic study WH Lo-Ciganic, JL Huang, HH Zhang, JC Weiss, CK Kwoh, JM Donohue, ... PloS one 15 (7), e0235981, 2020	40	2020
Fairness amidst non‐IID graph data: A literature review W Zhang, S Zhou, T Walsh, JC Weiss AI Magazine 46 (1), e12212, 2025	34	2025
Censored fairness through awareness W Zhang, T Hernandez-Boussard, J Weiss Proceedings of the AAAI conference on artificial intelligence 37 (12), 14611 …, 2023	33	2023
Fairness with censorship and group constraints W Zhang, JC Weiss Knowledge and Information Systems 65 (6), 2571-2594, 2023	33	2023
Multiplicative Forests for Continuous-Time Processes JC Weiss, S Natarajan, D Page Advances in Neural Information Processing Systems 25, 467-475, 2012	29	2012
Statistical Relational Learning to Predict Primary Myocardial Infarction from Electronic Health Records JC Weiss, S Natarajan, PL Peissig, C McCarty, D Page Twenty-Fourth IAAI Conference, 2012	26	2012
Fairness amidst non-iid graph data: Current achievements and future directions W Zhang, S Pan, S Zhou, T Walsh, JC Weiss arXiv preprint arXiv:2202.07170, 2022	21	2022
Individual fairness under uncertainty W Zhang, Z Wang, J Kim, C Cheng, T Oommen, P Ravikumar, J Weiss ECAI 2023, 3042-3049, 2023	18	2023
Harmonic-Mean Cox Models: A Ruler for Equal Attention to Risk X Wang, W Zhang, A Jadhav, W Jeremy C AAAI Symposium on Survival Prediction: Algorithms, Challenges, and Applications, 2021	15	2021

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