collaborators

9 papers

cs.AI2026

A safety-oriented hypothetico-deductive framework for AI-assisted differential diagnosis

Fan Ma, Mauro Giuffrè, Donald Wright +12

Diagnostic error is a major threat to patient safety, yet current large language model (LLM) systems often treat diagnosis as a one-shot prediction task, lacking safeguards against…

cs.AI2026

Foundation Models to Unlock Real-World Evidence from Nationwide Medical Claims

Fan Ma, Yuntian Liu, Xiang Lan +22

Evidence derived from large-scale real-world data (RWD) is increasingly informing regulatory evaluation and healthcare decision-making. Administrative claims provide population-sca…

cs.CL2026

Toward Federated Large Language Models in Medicine: A Parameter-Efficient Framework for Privacy-Preserving, Multi-Institutional Adaptation

Anran Li, Yuanyuan Chen, Wenjun Long +16

Large language models (LLMs) are increasingly adapted for medical applications, but most are trained using data from a single institution because privacy and governance constraints…

cs.CL2026

Memorization in Large Language Models in Medicine: Prevalence, Characteristics, and Implications

Anran Li, Lingfei Qian, Mengmeng Du +18

Large Language Models (LLMs) have demonstrated significant potential in medicine, with many studies adapting them through continued pre-training or fine-tuning on medical data to e…

q-bio.GN2025

Near-Lossless Model Compression Enables Longer Context Inference in DNA Large Language Models

Rui Zhu, Xiaopu Zhou, Haixu Tang +2

Trained on massive cross-species DNA corpora, DNA large language models (LLMs) learn the fundamental "grammar" and evolutionary patterns of genomic sequences. This makes them power…

cs.CL2025

LEME: Open Large Language Models for Ophthalmology with Advanced Reasoning and Clinical Validation

Hyunjae Kim, Xuguang Ai, Sahana Srinivasan +27

The rising prevalence of eye diseases poses a growing public health burden. Large language models (LLMs) offer a promising path to reduce documentation workload and support clinica…