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20242026
most citedEntry-level guide to the use of large language models for medical research

2 citations · 2 across the 2 of their papers we have counts for

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cs.CL2025

Towards Adapting Open-Source Large Language Models for Expert-Level Clinical Note Generation

Hanyin Wang, Chufan Gao, Bolun Liu +7

Proprietary Large Language Models (LLMs) such as GPT-4 and Gemini have demonstrated promising capabilities in clinical text summarization tasks. However, due to patient data privac…

cs.CL2025

GT2Vec: Large Language Models as Multi-Modal Encoders for Text and Graph-Structured Data

Jiacheng Lin, Kun Qian, Haoyu Han +9

Graph-structured information offers rich contextual information that can enhance language models by providing structured relationships and hierarchies, leading to more expressive e…

cs.CL2025

A foundation model for human-AI collaboration in medical literature mining

Zifeng Wang, Lang Cao, Qiao Jin +20

Systematic literature review is essential for evidence-based medicine, requiring comprehensive analysis of clinical trial publications. However, the application of artificial intel…

cs.CL2024

A Perspective for Adapting Generalist AI to Specialized Medical AI Applications and Their Challenges

Zifeng Wang, Hanyin Wang, Benjamin Danek +6

The integration of Large Language Models (LLMs) into medical applications has sparked widespread interest across the healthcare industry, from drug discovery and development to cli…

cs.CL2024

Accelerating Clinical Evidence Synthesis with Large Language Models

Zifeng Wang, Lang Cao, Benjamin Danek +3

Synthesizing clinical evidence largely relies on systematic reviews of clinical trials and retrospective analyses from medical literature. However, the rapid expansion of publicati…