Signals 4 · free daily AI digest

TRACER, a time-to-event EHR foundation model for disease detection across health systems

Paper recorded by Signals 4 on 2026-10-29 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-29 on arXiv · recorded by Signals 4 on 2026-10-30

Category: cs.LG · 机器学习 · first seen 2026-10-30

Abstract

Foundation models trained on longitudinal electronic health records (EHRs) can predict clinical diagnoses years in the future, making them a potential tool for disease screening. We developed TRACER (Temporal Risk Assessment with Clinical EHR Representations), a decoder-based foundation model pretrained on data from over 4.5 million patients from four health systems, and evaluated it on 16 inciden

Read on arXiv →

#74 most recent of 703 cs.LG papers we have recorded · ↑ newer: Machine Learning-Based Detection of Mobile Money Scan Messages in Ghan · ↓ older: Homebrewed SLMs: Autoregressive and Masked Diffusion Language Models B
Cite this page: TRACER, a time-to-event EHR foundation model for disease detection across health systems: the #74 most recent of 703 cs.LG papers we have recorded (as of 2026-10-29). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/tracer-a-time-to-event-ehr-foundation-model-for-disease-detection-across-health-.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
Related: More cs.LG papers · arXiv signals · All papers · Today in AI
Get 4 AI signals a day by email — free.
Subscribe free → See all plans →
Get 4 AI signals a day by email — free
All models · All repos · By company · Daily editions