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20242026
most citedInformation Extraction from Clinical Notes: Are We Ready to Switch to Large Language Models?

9 citations · 29 across the 9 of their papers we have counts for

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7 papers · 1 filter

cs.CL2026

Evaluating Multi-Turn Multimodal Diagnostic Reasoning on Challenging Real-World Clinical Cases

Rui Yang, Weihao Xuan, Yi Lin +23

Clinical diagnostic evaluation should not only assess whether models can provide correct diagnoses, but also reflect the realities of clinical practice, including progressive discl…

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.CL2024★ 9 cited

Information Extraction from Clinical Notes: Are We Ready to Switch to Large Language Models?

Yan Hu, Xu Zuo, Yujia Zhou +9

Backgrounds: Information extraction (IE) is critical in clinical natural language processing (NLP). While large language models (LLMs) excel on generative tasks, their performance…

cs.CL2024★ 3 cited

Suicide Phenotyping from Clinical Notes in Safety-Net Psychiatric Hospital Using Multi-Label Classification with Pre-Trained Language Models

Zehan Li, Yan Hu, Scott Lane +7

Accurate identification and categorization of suicidal events can yield better suicide precautions, reducing operational burden, and improving care quality in high-acuity psychiatr…

cs.CL2024★ 1 cited

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…

cs.CL2024★ 7 cited

Enhancing Large Language Models with Domain-specific Retrieval Augment Generation: A Case Study on Long-form Consumer Health Question Answering in Ophthalmology

Aidan Gilson, Xuguang Ai, Thilaka Arunachalam +19

Despite the potential of Large Language Models (LLMs) in medicine, they may generate responses lacking supporting evidence or based on hallucinated evidence. While Retrieval Augmen…

cs.CL2024★ 8 cited

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…