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20242026
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cs.CL2026

MedAction: Towards Active Multi-turn Clinical Diagnostic LLMs

Hsin-Ling Hsu, Zizheng Wang, Donghua Zhang +9

Most existing LLM diagnoses are evaluated on static, single-turn settings where complete patient information is provided upfront, an oversimplification of real clinical practice. W…

cs.CL20262 cited

MedPlan: A Two-Stage RAG-Based System for Personalized Medical Plan Generation

Hsin-Ling Hsu, Cong-Tinh Dao, Luning Wang +12

Despite recent success in applying large language models (LLMs) to electronic health records (EHR), most systems focus primarily on assessment rather than treatment planning. We id…

cs.CL2024

Multi-OphthaLingua: A Multilingual Benchmark for Assessing and Debiasing LLM Ophthalmological QA in LMICs

David Restrepo, Chenwei Wu, Zhengxu Tang +14

Current ophthalmology clinical workflows are plagued by over-referrals, long waits, and complex and heterogeneous medical records. Large language models (LLMs) present a promising…

cs.CL2024

Large Language Multimodal Models for 5-Year Chronic Disease Cohort Prediction Using EHR Data

Jun-En Ding, Phan Nguyen Minh Thao, Wen-Chih Peng +10

Chronic diseases such as diabetes are the leading causes of morbidity and mortality worldwide. Numerous research studies have been attempted with various deep learning models in di…

cs.CL2024

MEDFuse: Multimodal EHR Data Fusion with Masked Lab-Test Modeling and Large Language Models

Thao Minh Nguyen Phan, Cong-Tinh Dao, Chenwei Wu +7

Electronic health records (EHRs) are multimodal by nature, consisting of structured tabular features like lab tests and unstructured clinical notes. In real-life clinical practice,…