8 citations · 12 across the 10 of their papers we have counts for
10 papers
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…
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…
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…
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…
Supporting Patients in Managing Electronic Health Records and Biospecimens Consent for Research: Insights from a Mixed-Methods Usability Evaluation of the iAGREE Portal
Di Hu, Xi Lu, Yunan Chen +6
De-identified health data are frequently used in research. As AI advances heighten the risk of re-identification, it is important to respond to concerns about transparency, data pr…
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…
Enhancing Patient-Centric Communication: Leveraging LLMs to Simulate Patient Perspectives
Xinyao Ma, Rui Zhu, Zihao Wang +5
Large Language Models (LLMs) have demonstrated impressive capabilities in role-playing scenarios, particularly in simulating domain-specific experts using tailored prompts. This ab…
ByzSFL: Achieving Byzantine-Robust Secure Federated Learning with Zero-Knowledge Proofs
Yongming Fan, Rui Zhu, Zihao Wang +5
The advancement of AI models, especially those powered by deep learning, faces significant challenges in data-sensitive industries like healthcare and finance due to the distribute…
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…
Me LLaMA: Foundation Large Language Models for Medical Applications
Qianqian Xie, Qingyu Chen, Aokun Chen +15
Recent advancements in large language models (LLMs) like ChatGPT and LLaMA show promise in medical applications, yet challenges remain in medical language comprehension. This study…