most citedQuality of Answers of Generative Large Language Models vs Peer Patients for Interpreting Lab Test Results for Lay Patients: Evaluation Study

56 citations · 59 across the 3 of their papers we have counts for

collaborators

5 papers

cs.AI2024

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…

cs.AI2024

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…

cs.CL202456 cited

Quality of Answers of Generative Large Language Models vs Peer Patients for Interpreting Lab Test Results for Lay Patients: Evaluation Study

Zhe He, Balu Bhasuran, Qiao Jin +6

Lab results are often confusing and hard to understand. Large language models (LLMs) such as ChatGPT have opened a promising avenue for patients to get their questions answered. We…

cs.CL20243 cited

PubTator 3.0: an AI-powered Literature Resource for Unlocking Biomedical Knowledge

Chih-Hsuan Wei, Alexis Allot, Po-Ting Lai +7

PubTator 3.0 (https://www.ncbi.nlm.nih.gov/research/pubtator3/) is a biomedical literature resource using state-of-the-art AI techniques to offer semantic and relation searches for…

cs.IR2024

Information Retrieval and Classification of Real-Time Multi-Source Hurricane Evacuation Notices

Tingting Zhao, Shubo Tian, Jordan Daly +3

For an approaching disaster, the tracking of time-sensitive critical information such as hurricane evacuation notices is challenging in the United States. These notices are issued…