72 citations · 108 across the 32 of their papers we have counts for
7 papers · 1 filter
Prediction bias in biological ageing markers
Yiqun Lin, Ariel Yuhan Ong, Matthew Yu Heng Wong +52
Biological ageing markers have attracted growing interest, with models estimating age from organ imaging or blood biomarkers. An estimated age above chronological age or the age-sp…
A specialized reasoning large language model for accelerating rare disease diagnosis: a randomized AI physician assistance trial
Haichao Chen, Songchi Zhou, Zhengyun Zhao +28
Rare diseases affect millions of individuals worldwide, yet timely diagnosis remains a major public health challenge due to scarcity of specialized clinical expertise. While large…
Resolving the bias-precision paradox with stochastic causal representation learning for personalized medicine
Peisong Zhang, Manqiang Peng, Yuxuan Wu +21
Estimating individualized treatment effects from longitudinal observational data is central to data-driven medicine, yet existing methods face a fundamental limitation: reducing co…
VOLMO: Versatile and Open Large Models for Ophthalmology
Zhenyue Qin, Younjoon Chung, Elijah Lee +16
Vision impairment affects millions globally, and early detection is critical to preventing irreversible vision loss. Ophthalmology workflows require clinicians to integrate medical…
Deliberative multi-agent large language models improve clinical reasoning in ophthalmology
Ehsan Misaghi, Sean T Berkowitz, Bing Yu Chen +10
Large language models (LLMs) show potential for ophthalmic clinical reasoning, yet individual models risk introducing harm. We evaluated whether multi-agent LLM deliberative counci…
EyeWorld: A Generative World Model of Ocular State and Dynamics
Ziyu Gao, Xinyuan Wu, Xiaolan Chen +10
Ophthalmic decision-making depends on subtle lesion-scale cues interpreted across multimodal imaging and over time, yet most medical foundation models remain static and degrade und…
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…