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Scott A Malec

Showing results (1-10 of 10) with videos related to

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AMIA Joint Summits on Translational Science Proceedings. AMIA Joint Summits on Translational Science|June 2, 2020
Exploring Novel Computable Knowledge in Structured Drug Product LabelsScott A Malec, Richard D Boyce
Journal of Biomedical Informatics|March 15, 2021
Using computable knowledge mined from the literature to elucidate confounders for EHR-based pharmacovigilanceScott A Malec, Peng Wei, Elmer V Bernstam, et al.
AMIA ... Annual Symposium Proceedings. AMIA Symposium|March 9, 2017
Literature-Based Discovery of Confounding in Observational Clinical DataScott A Malec, Peng Wei, Hua Xu, et al.
Medrxiv : the Preprint Server for Health Sciences|June 29, 2026
A Pilot Project Leveraging Large Language Models for Automated Screening and Variable Extraction in Observational StudiesManjil M Pradhan, Rajesh Upadhayaya, Sarah C Wenyon, et al.
Journal of Biomedical Informatics|April 22, 2023
Causal feature selection using a knowledge graph combining structured knowledge from the biomedical literature and ontologies: A use case studying depression as a risk factor for Alzheimer's diseaseScott A Malec, Sanya B Taneja, Steven M Albert, et al.
Medrxiv : the Preprint Server for Health Sciences|November 26, 2025
Predicting Alzheimer's Disease Diagnosis, a Decade or more Years before Onset using the Electronic Health Record and Random Forest Machine Learning ModelsSanya B Taneja, Richard D Boyce, Scott A Malec, et al.
IEEE Journal of Biomedical and Health Informatics|March 3, 2025
Detecting Opioid Use Disorder in Health Claims Data With Positive Unlabeled LearningPraveen Kumar, Fariha Moomtaheen, Scott A Malec, et al.
Journal of Medical Internet Research|April 19, 2026
Detecting Uncoded Self-Harm in Veterans' Electronic Health Records Using Positive and Unlabeled Learning: Retrospective Observational StudyPraveen Kumar, Alexandria D Viszolay, Rajesh Upadhayaya, et al.
Journal of Medical Internet Research|June 4, 2026
Detecting Uncoded Self-Harm in Veterans' Electronic Health Records Using Positive and Unlabeled Learning: Retrospective Cohort StudyPraveen Kumar, Alexandria D Viszolay, Rajesh Upadhayaya, et al.
Scientific Data|April 11, 2024
An open source knowledge graph ecosystem for the life sciencesTiffany J Callahan, Ignacio J Tripodi, Adrianne L Stefanski, et al.
Pageof 1

Showing results (1-10 of 10) with videos related to

Sort By:
Pageof 1
AMIA Joint Summits on Translational Science Proceedings. AMIA Joint Summits on Translational Science|June 2, 2020
Exploring Novel Computable Knowledge in Structured Drug Product LabelsScott A Malec, Richard D Boyce
Journal of Biomedical Informatics|March 15, 2021
Using computable knowledge mined from the literature to elucidate confounders for EHR-based pharmacovigilanceScott A Malec, Peng Wei, Elmer V Bernstam, et al.
AMIA ... Annual Symposium Proceedings. AMIA Symposium|March 9, 2017
Literature-Based Discovery of Confounding in Observational Clinical DataScott A Malec, Peng Wei, Hua Xu, et al.
Medrxiv : the Preprint Server for Health Sciences|June 29, 2026
A Pilot Project Leveraging Large Language Models for Automated Screening and Variable Extraction in Observational StudiesManjil M Pradhan, Rajesh Upadhayaya, Sarah C Wenyon, et al.
Journal of Biomedical Informatics|April 22, 2023
Causal feature selection using a knowledge graph combining structured knowledge from the biomedical literature and ontologies: A use case studying depression as a risk factor for Alzheimer's diseaseScott A Malec, Sanya B Taneja, Steven M Albert, et al.
Medrxiv : the Preprint Server for Health Sciences|November 26, 2025
Predicting Alzheimer's Disease Diagnosis, a Decade or more Years before Onset using the Electronic Health Record and Random Forest Machine Learning ModelsSanya B Taneja, Richard D Boyce, Scott A Malec, et al.
IEEE Journal of Biomedical and Health Informatics|March 3, 2025
Detecting Opioid Use Disorder in Health Claims Data With Positive Unlabeled LearningPraveen Kumar, Fariha Moomtaheen, Scott A Malec, et al.
Journal of Medical Internet Research|April 19, 2026
Detecting Uncoded Self-Harm in Veterans' Electronic Health Records Using Positive and Unlabeled Learning: Retrospective Observational StudyPraveen Kumar, Alexandria D Viszolay, Rajesh Upadhayaya, et al.
Journal of Medical Internet Research|June 4, 2026
Detecting Uncoded Self-Harm in Veterans' Electronic Health Records Using Positive and Unlabeled Learning: Retrospective Cohort StudyPraveen Kumar, Alexandria D Viszolay, Rajesh Upadhayaya, et al.
Scientific Data|April 11, 2024
An open source knowledge graph ecosystem for the life sciencesTiffany J Callahan, Ignacio J Tripodi, Adrianne L Stefanski, et al.
Pageof 1