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Author Details

Jeremy C Weiss
Carnegie Mellon University
2012
17
6
PMIDPaper TitleJournal TitlePublished Year
37128459Learning Clinical Concepts for Predicting Risk of Progression to Severe COVID-19.AMIA Annu Symp Proc2023
35308980Unpacking the Drop in COVID-19 Case Fatality Rates: A Study of National and Florida Line-Level Data.AMIA Annu Symp Proc2022
35623798Developing and validating a machine-learning algorithm to predict opioid overdose in Medicaid beneficiaries in two US states: a prognostic modelling study.Lancet Digit Health2022
35713860Biomedical Literature Mining for Repurposing Laboratory Tests.Methods Mol Biol2022
35315173Changes in predicted opioid overdose risk over time in a state Medicaid program: a group-based trajectory modeling analysis.Addiction2022
33481168Predicting Mortality Risk After a Hospital or Emergency Department Visit for Nonfatal Opioid Overdose.J Gen Intern Med2021
33169861Machine-learning algorithms for predicting hospital re-admissions in sickle cell disease.Br J Haematol2021
32308834Hypersphere clustering to characterize healthcare providers using prescriptions and procedures from Medicare claims data.AMIA Annu Symp Proc2020
32043261Occupational Patterns of Opioid-Related Overdose Deaths Among Arizona Medicaid Enrollees, 2008-2017.J Gen Intern Med2020
32661034Using Machine Learning to Predict Primary Care and Advance Workforce Research.Ann Fam Med2020
32678860Using machine learning to predict risk of incident opioid use disorder among fee-for-service Medicare beneficiaries: A prognostic study.PLoS One2020
30901048Evaluation of Machine-Learning Algorithms for Predicting Opioid Overdose Risk Among Medicare Beneficiaries With Opioid Prescriptions.JAMA Netw Open2019
31259012Machine Learning Assisted Discovery of Novel Predictive Lab Tests Using Electronic Health Record Data.AMIA Jt Summits Transl Sci Proc2019
31104070Derivation, Validation, and Potential Treatment Implications of Novel Clinical Phenotypes for Sepsis.JAMA2019
26958271Machine Learning for Treatment Assignment: Improving Individualized Risk Attribution.AMIA Annu Symp Proc2015
25360347Statistical Relational Learning to Predict Primary Myocardial Infarction from Electronic Health Records.Proc Innov Appl Artif Intell Conf2012
25284967Multiplicative Forests for Continuous-Time Processes.Adv Neural Inf Process Syst2012
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Collaborators

Adam J Gordon
Clinical Care, University of Utah School of Medicine
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Peggy L Peissig
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Co-authored papers 2
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AWB) Center for Professionalism & Value in Health Care
Co-authored papers 1
G Clermont
University of Pittsburgh
Co-authored papers 1
Chung-Chou H Chang
Graduate School of Public Health, University of Pittsburgh
Co-authored papers 1
Scott M Berry
University of Kansas Medical Center
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Mehdi Nouraie
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Qi Mi
University of Pittsburgh
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Catherine A McCarty
University of Minnesota Medical School, 1035 University Drive duluth
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Zhongying Xu
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Yonghui Wu
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Jason N Kennedy
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Donald M Yealy
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Hernando Gomez
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Center for Experimental and Molecular Medicine, University of Amsterdam
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Corrine F Elliott
University of Kentucky
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Steven M Opal
Infectious Disease Division at Brown University Warren Alpert Medical School
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Derek C Angus
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Victor B Talisa
University of Pittsburgh School of Medicine
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Ron Stewart
Co-authored papers 1
David T Huang
University of Pittsburgh School of Medicine
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Stephen Petterson
Robert Graham Center for Policy Studies in Family Medicine and Primary Care
Co-authored papers 1
Christopher W Seymour
University of Pittsburgh
Co-authored papers 1
John A Kellum
Spectral Medical Inc.
Co-authored papers 1
Sachin Yende
Clinical Research
Co-authored papers 1
Shu Wang
University of Florida
Co-authored papers 1
Release 1.2