83 citations · 150 across the 6 of their papers we have counts for
6 papers
Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium
Hyewon Jeong, Sarah Jabbour, Yuzhe Yang +40
The third ML4H symposium was held in person on December 10, 2023, in New Orleans, Louisiana, USA. The symposium included research roundtable sessions to foster discussions between…
CEHR-GPT: Generating Electronic Health Records with Chronological Patient Timelines
Chao Pang, Xinzhuo Jiang, Nishanth Parameshwar Pavinkurve +8
Synthetic Electronic Health Records (EHR) have emerged as a pivotal tool in advancing healthcare applications and machine learning models, particularly for researchers without dire…
Causal Fairness Assessment of Treatment Allocation with Electronic Health Records
Linying Zhang, Lauren R. Richter, Yixin Wang +4
Healthcare continues to grapple with the persistent issue of treatment disparities, sparking concerns regarding the equitable allocation of treatments in clinical practice. While v…
Adjusting for indirectly measured confounding using large-scale propensity scores
Linying Zhang, Yixin Wang, Martijn Schuemie +2
Confounding remains one of the major challenges to causal inference with observational data. This problem is paramount in medicine, where we would like to answer causal questions f…
The Medical Deconfounder: Assessing Treatment Effects with Electronic Health Records
Linying Zhang, Yixin Wang, Anna Ostropolets +3
The treatment effects of medications play a key role in guiding medical prescriptions. They are usually assessed with randomized controlled trials (RCTs), which are expensive. Rece…
Evaluating Reinforcement Learning Algorithms in Observational Health Settings
Omer Gottesman, Fredrik Johansson, Joshua Meier +16
Much attention has been devoted recently to the development of machine learning algorithms with the goal of improving treatment policies in healthcare. Reinforcement learning (RL)…