Showing 1–20 of 22 results
/ Date/ Name
Jul 14, 2019Counterfactual Reasoning for Fair Clinical Risk PredictionSep 12, 2018Creating Fair Models of Atherosclerotic Cardiovascular Disease RiskJul 20, 2020An Empirical Characterization of Fair Machine Learning For Clinical Risk PredictionMar 18, 2024A Toolbox for Surfacing Health Equity Harms and Biases in Large Language ModelsFeb 3, 2022Net benefit, calibration, threshold selection, and training objectives for algorithmic fairness in healthcareNov 13, 2019Federated and Differentially Private Learning for Electronic Health RecordsAug 27, 2021A comparison of approaches to improve worst-case predictive model performance over patient subpopulationsDec 21, 2022Adapting to Latent Subgroup Shifts via Concepts and ProxiesJun 4, 2025Understanding challenges to the interpretation of disaggregated evaluations of algorithmic fairnessAug 9, 2018The Effectiveness of Multitask Learning for Phenotyping with Electronic Health Records DataSep 4, 2024Nteasee: Understanding Needs in AI for Health in Africa -- A Mixed-Methods Study of Expert and General Population PerspectivesOct 17, 2025Reflections from Research Roundtables at the Conference on Health, Inference, and Learning (CHIL) 2025Dec 2, 2018Predicting Inpatient Discharge Prioritization With Electronic Health RecordsNov 30, 2021A collection of the accepted abstracts for the Machine Learning for Health (ML4H) symposium 2021Dec 26, 2022Large Language Models Encode Clinical KnowledgeMar 5, 2024The Case for Globalizing Fairness: A Mixed Methods Study on Colonialism, AI, and Health in AfricaMay 16, 2023Towards Expert-Level Medical Question Answering with Large Language ModelsDec 14, 2023Helping or Herding? Reward Model Ensembles Mitigate but do not Eliminate Reward HackingJan 6, 2020Language Models Are An Effective Patient Representation Learning Technique For Electronic Health Record DataMar 12, 2024Proxy Methods for Domain Adaptation