89 citations · 148 across the 23 of their papers we have counts for
24 papers
Agents' Last Exam
Yiyou Sun, Xinyang Han, Weichen Zhang +355
Recent AI systems have achieved strong results on a wide range of benchmarks, yet these gains have not translated into economically meaningful deployment across many professional d…
Med-V1: Small Language Models for Zero-shot and Scalable Biomedical Evidence Attribution
Qiao Jin, Yin Fang, Lauren He +12
Assessing whether an article supports an assertion is essential for hallucination detection and claim verification. While large language models (LLMs) have the potential to automat…
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…
Ensuring Safety and Trust: Analyzing the Risks of Large Language Models in Medicine
Yifan Yang, Qiao Jin, Robert Leaman +15
The remarkable capabilities of Large Language Models (LLMs) make them increasingly compelling for adoption in real-world healthcare applications. However, the risks associated with…
Humans and Large Language Models in Clinical Decision Support: A Study with Medical Calculators
Nicholas Wan, Qiao Jin, Joey Chan +8
Although large language models (LLMs) have been assessed for general medical knowledge using licensing exams, their ability to support clinical decision-making, such as selecting m…
Evaluating the Impact of Lab Test Results on Large Language Models Generated Differential Diagnoses from Clinical Case Vignettes
Balu Bhasuran, Qiao Jin, Yuzhang Xie +6
Differential diagnosis is crucial for medicine as it helps healthcare providers systematically distinguish between conditions that share similar symptoms. This study assesses the i…
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…
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…
Improving Retrieval-Augmented Generation in Medicine with Iterative Follow-up Questions
Guangzhi Xiong, Qiao Jin, Xiao Wang +3
The emergent abilities of large language models (LLMs) have demonstrated great potential in solving medical questions. They can possess considerable medical knowledge, but may stil…
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…
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…
Benchmarking Retrieval-Augmented Generation for Medicine
Guangzhi Xiong, Qiao Jin, Zhiyong Lu +1
While large language models (LLMs) have achieved state-of-the-art performance on a wide range of medical question answering (QA) tasks, they still face challenges with hallucinatio…
AgentMD: Empowering Language Agents for Risk Prediction with Large-Scale Clinical Tool Learning
Qiao Jin, Zhizheng Wang, Yifan Yang +8
Clinical calculators play a vital role in healthcare by offering accurate evidence-based predictions for various purposes such as prognosis. Nevertheless, their widespread utilizat…
Harnessing PubMed User Query Logs for Post Hoc Explanations of Recommended Similar Articles
Ashley Shin, Qiao Jin, James Anibal +1
Searching for a related article based on a reference article is an integral part of scientific research. PubMed, like many academic search engines, has a "similar articles" feature…
Unmasking and Quantifying Racial Bias of Large Language Models in Medical Report Generation
Yifan Yang, Xiaoyu Liu, Qiao Jin +2
Large language models like GPT-3.5-turbo and GPT-4 hold promise for healthcare professionals, but they may inadvertently inherit biases during their training, potentially affecting…
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…