7 citations · 10 across the 9 of their papers we have counts for
9 papers
HealMed: Multilingual Evaluation of Large Language Models in Medicine
Yingjian Chen, Fan Gao, Sherry T. Tong +42
We present HealMed, an expert-reviewed benchmark for multilingual evaluation of large language models in medicine. HealMed contains 1,000 examples in each of nine languages, drawn…
MedPMC: A Systematic Framework for Scaling High-Fidelity Medical Multimodal Data for Foundation Models
Hyunjae Kim, Dain Kim, Pan Xiao +25
Medicine is inherently multimodal, requiring clinicians to synthesize information across diverse data streams. Yet the development of multimodal foundation models is constrained by…
Large Language Models Lack Temporal Awareness of Medical Knowledge
Zihan Guan, Qiao Jin, Guangzhi Xiong +6
The existing methods for evaluating the medical knowledge of Large Language Models (LLMs) are largely based on atemporal examination-style benchmarks, while in reality, medical kno…
Are Multimodal LLMs Ready for Clinical Dermatology? A Real-World Evaluation in Dermatology
Roy Jiang, Hyunjae Kim, Zhenyue Qin +8
Multimodal large language models (MLLMs) have demonstrated promise on publicly available dermatology benchmarks. However, benchmark performance may not generalize to real-world der…
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…
Humans and Large Language Models in Clinical Decision Support: A Study with Medical Calculators
Nicholas Wan, Qiao Jin, Joey Chan +8
Although large language models (LLMs) have been assessed for general medical knowledge using licensing exams, their ability to support clinical decision-making, such as selecting m…
MedINST: Meta Dataset of Biomedical Instructions
Wenhan Han, Meng Fang, Zihan Zhang +5
The integration of large language model (LLM) techniques in the field of medical analysis has brought about significant advancements, yet the scarcity of large, diverse, and well-a…
Entry-level guide to the use of large language models for medical research
Qiao Jin, Nicholas Wan, Robert Leaman +20
Frontier large language models (LLMs), such as GPT-5, Claude 4.5, Gemini 3, Llama 4, and DeepSeek-R1, represent a transformative class of AI tools capable of revolutionizing variou…
Augmenting Biomedical Named Entity Recognition with General-domain Resources
Yu Yin, Hyunjae Kim, Xiao Xiao +6
Training a neural network-based biomedical named entity recognition (BioNER) model usually requires extensive and costly human annotations. While several studies have employed mult…