124 citations · 345 across the 33 of their papers we have counts for
6 papers · 1 filter
Developing Large Language Models for Clinical Research Using One Million Clinical Trials
Zifeng Wang, Jiacheng Lin, Qiao Jin +5
Developing artificial intelligence (AI) for clinical research requires a comprehensive data foundation that supports model training and rigorous evaluation. Here, we introduce Tria…
Beyond Multiple-Choice Accuracy: Real-World Challenges of Implementing Large Language Models in Healthcare
Yifan Yang, Qiao Jin, Qingqing Zhu +5
Large Language Models (LLMs) have gained significant attention in the medical domain for their human-level capabilities, leading to increased efforts to explore their potential in…
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…
Adversarial Attacks on Large Language Models in Medicine
Yifan Yang, Qiao Jin, Furong Huang +1
The integration of Large Language Models (LLMs) into healthcare applications offers promising advancements in medical diagnostics, treatment recommendations, and patient care. Howe…
GeneAgent: Self-verification Language Agent for Gene Set Knowledge Discovery using Domain Databases
Zhizheng Wang, Qiao Jin, Chih-Hsuan Wei +6
Gene set knowledge discovery is essential for advancing human functional genomics. Recent studies have shown promising performance by harnessing the power of Large Language Models…
Leveraging Generative AI for Clinical Evidence Summarization Needs to Ensure Trustworthiness
Gongbo Zhang, Qiao Jin, Denis Jered McInerney +11
Evidence-based medicine promises to improve the quality of healthcare by empowering medical decisions and practices with the best available evidence. The rapid growth of medical ev…