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20242026
most citedUnmasking and Quantifying Racial Bias of Large Language Models in Medical Report Generation

89 citations · 148 across the 23 of their papers we have counts for

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15 papers · 1 filter

cs.CL2024★ 3 cited

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…

cs.CL2024★ 1 cited

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…

cs.CL2024

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…

cs.AI2024

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…

cs.AI2024★ 2 cited

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.CL2024★ 7 cited

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…

cs.CL2024★ 5 cited

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…

cs.CL2024★ 7 cited

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…

cs.AI2024★ 5 cited

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…

cs.AI2024★ 2 cited

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.CL2024★ 23 cited

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…

cs.CL2024

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…

cs.IR2024

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…

cs.CL2024★ 89 cited

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…

cs.CL2024★ 3 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…