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20242026
most citedA survey of recent methods for addressing AI fairness and bias in biomedicine

98 citations · 107 across the 10 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

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.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.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.AI2024★ 98 cited

A survey of recent methods for addressing AI fairness and bias in biomedicine

Yifan Yang, Mingquan Lin, Han Zhao +3

Artificial intelligence (AI) systems have the potential to revolutionize clinical practices, including improving diagnostic accuracy and surgical decision-making, while also reduci…