most citedEvent-Based Contrastive Learning for Medical Time Series

2 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CY2026

Rare Diseases, Common Dilemmas: LLMs Prioritize Equal Resource Distribution over Patient Benefit in Decision-Making

Minda Zhao, Xu Han, Rishabh Goel +6

Clinical decision-making often involves prioritizing ethical values, such as beneficence, non-maleficence, respecting a patient's autonomy, and justice. Recent work has begun to as…

cs.AI2026

What Does the AI Doctor Value? Auditing Pluralism in the Clinical Ethics of Language Models

Payal Chandak, Victoria Alkin, David Wu +11

Medicine is inherently pluralistic. Principles such as autonomy, beneficence, nonmaleficence, and justice routinely conflict, and such ethical dilemmas often sharply divide reasona…

cs.AI2026

EveryQuery: A Promptable Foundation Model for Clinical Prediction Tasks over Electronic Health Records

Payal Chandak, Gregory Kondas, Liat Antwarg Friedman +2

Autoregressive foundation models for electronic health records can make predictions for diverse clinical tasks without finetuning. These methods work by generating possible "synthe…

cs.LG2023★ 2 cited

Event-Based Contrastive Learning for Medical Time Series

Hyewon Jeong, Nassim Oufattole, Matthew Mcdermott +4

In clinical practice, one often needs to identify whether a patient is at high risk of adverse outcomes after some key medical event. For example, quantifying the risk of adverse o…

cs.LG2023★ 1 cited

Sequential Multi-Dimensional Self-Supervised Learning for Clinical Time Series

Aniruddh Raghu, Payal Chandak, Ridwan Alam +2

Self-supervised learning (SSL) for clinical time series data has received significant attention in recent literature, since these data are highly rich and provide important informa…