In-context: August 18, 2025
In-context: August 18, 2025
Here’s a quick wrap of the three papers we found interesting over the last few weeks with some take home points.
00:30 - An Electrocardiogram Foundation Model Built on over 10 Million Recordings
07:10 - Zero-shot Large Language Models for Long Clinical Text Summarization with Temporal Reasoning
14:15 - Diagnostic Codes in AI prediction models and Label Leakage of Same-admission Clinical Outcomes
16:50 - Evaluating reasoning LLMs’ potential to perpetuate racial and gender disease stereotypes in healthcare
Some resources and papers we discuss:
Li J et al, 2025 “An Electrocardiogram Foundation Model Built on over 10 Million Recordings”, NEJM AI 2025;2(7), DOI: 10.1056/AIoa2401033
Kruse, M et al. “Zero-shot Large Language Models for Long Clinical Text Summarization with Temporal Reasoning.” ArXiv abs/2501.18724 (2025)
Ramadan, B et al. 2025 “Diagnostic Codes in AI prediction models and Label Leakage of Same-admission Clinical Outcomes” medRxiv 2025.08.09.25333360; doi: https://doi.org/10.1101/2025.08.09.25333360
Docking J. et al. 2025 “Evaluating reasoning LLMs’ potential to perpetuate racial and gender disease stereotypes in healthcare”, medRxiv 2025.08.05.25333007; doi: https://doi.org/10.1101/2025.08.05.25333007
Coalition for Healthcare AI, Testing and Evaluation (T&E) Framework https://rai-content.chai.org/en/latest/patient-discharge-summarization/te.html