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20112026
most citedOpportunities and Challenges for ChatGPT and Large Language Models in Biomedicine and Health

372 citations

20 papers

q-bio.BM2026★ 1 cited

Fold-switching proteins push the boundaries of conformational ensemble prediction

Myeongsang Lee, Lauren L. Porter

A protein's function depends critically on its conformational ensemble, a collection of energy weighted structures whose balance depends on temperature and environment. Though rece…

cs.CL2025

Repurposing Annotation Guidelines to Instruct LLM Annotators: A Case Study

Kon Woo Kim, Rezarta Islamaj, Jin-Dong Kim +2

This study investigates how existing annotation guidelines can be repurposed to instruct large language model (LLM) annotators for text annotation tasks. Traditional guidelines are…

cs.CV2025★ 2 cited

LMOD+: A Comprehensive Multimodal Dataset and Benchmark for Developing and Evaluating Multimodal Large Language Models in Ophthalmology

Zhenyue Qin, Yang Liu, Yu Yin +13

Vision-threatening eye diseases pose a major global health burden, with timely diagnosis limited by workforce shortages and restricted access to specialized care. While multimodal…

cs.CL2025★ 1 cited

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…

cs.CY2024★ 10 cited

Environment Scan of Generative AI Infrastructure for Clinical and Translational Science

Betina Idnay, Zihan Xu, William G. Adams +54

This study reports a comprehensive environmental scan of the generative AI (GenAI) infrastructure in the national network for clinical and translational science across 36 instituti…

eess.IV2024★ 13 cited

AI Workflow, External Validation, and Development in Eye Disease Diagnosis

Qingyu Chen, Tiarnan D L Keenan, Elvira Agron +35

Timely disease diagnosis is challenging due to increasing disease burdens and limited clinician availability. AI shows promise in diagnosis accuracy but faces real-world applicatio…