89 citations · 148 across the 23 of their papers we have counts for
7 papers · 1 filter
DeepEvidence: Empowering Biomedical Discovery with Deep Knowledge Graph Research
Zifeng Wang, Zheng Chen, Ziwei Yang +5
Biomedical knowledge graphs (KGs) encode vast, heterogeneous information spanning literature, genes, pathways, drugs, diseases, and clinical trials, but leveraging them collectivel…
Gene-R1: Reasoning with Data-Augmented Lightweight LLMs for Gene Set Analysis
Zhizheng Wang, Yifan Yang, Qiao Jin +1
The gene set analysis (GSA) is a foundational approach for uncovering the molecular functions associated with a group of genes. Recently, LLM-powered methods have emerged to annota…
Knowledge-guided Contextual Gene Set Analysis Using Large Language Models
Zhizheng Wang, Chi-Ping Day, Chih-Hsuan Wei +9
Gene set analysis (GSA) is a foundational approach for interpreting genomic data of diseases by linking genes to biological processes. However, conventional GSA methods overlook cl…
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…
Recommending Clinical Trials for Online Patient Cases using Artificial Intelligence
Joey Chan, Qiao Jin, Nicholas Wan +3
Clinical trials are crucial for assessing new treatments; however, recruitment challenges - such as limited awareness, complex eligibility criteria, and referral barriers - hinder…
Supervising the search process produces reliable and generalizable information-seeking agents
Guangzhi Xiong, Qiao Jin, Xiao Wang +9
Large language models (LLMs) are transforming web search by shifting from document ranking to synthesizing answers, and are increasingly deployed as autonomous agentic search syste…
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…