RELEAP: reinforcement-enhanced label-efficient active phenotyping for electronic health records

Reinforcement-enhanced label-efficient optimizes phenotype correction through downstream feedback, offering a scalable, label-efficient paradigm that reduces manual chart review and enhances the reliability of EHR-based risk prediction.

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Publication Details

Journal
JAMIA Open
Published
2026-01-06
DOI
https://doi.org/10.1093/jamiaopen/ooag019
Primary Topic
Machine Learning in Healthcare
Type
article
Field-Weighted Citation Impact
0.00
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article

RELEAP: reinforcement-enhanced label-efficient active phenotyping for electronic health records

Doudou Zhou, 弘道 新井川, Bibhas Ranjan Chakraborty, Kathryn I. Pollak et al.
JAMIA Open
Machine Learning in Healthcare
article

RELEAP: reinforcement-enhanced label-efficient active phenotyping for electronic health records

Doudou Zhou, 弘道 新井川, Bibhas Ranjan Chakraborty, Kathryn I. Pollak, Molei Liu, Yang Yang
article en

Abstract

Reinforcement-enhanced label-efficient optimizes phenotype correction through downstream feedback, offering a scalable, label-efficient paradigm that reduces manual chart review and enhances the reliability of EHR-based risk prediction.

JAMIA OpenVol. 9(1)
National University of Singapore (SG), Duke University (US), Peking University (CN), Prevention Institute (US), Peking University International Hospital (CN), Beijing International Studies University (CN)
Gender equality
Openalex Percentile: Top 53%
Machine Learning in Healthcare
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