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20242026
most citedPubTator 3.0: an AI-powered Literature Resource for Unlocking Biomedical Knowledge

3 citations · 7 across the 14 of their papers we have counts for

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6 papers · 1 filter

cs.AI2026

Large Language Models Meet Biomedical Knowledge Graphs for Mechanistically Grounded Therapeutic Prioritization

Chih-Hsuan Wei, Chi-Ping Day, Zhizheng Wang +8

Drug repurposing is often framed as a candidate identification task, but existing approaches provide limited guidance for distinguishing biologically plausible candidates from hist…

cs.AI2026

DeepER-Med: Advancing Deep Evidence-Based Research in Medicine Through Agentic AI

Zhizheng Wang, Chih-Hsuan Wei, Joey Chan +19

Trustworthiness and transparency are essential for the clinical adoption of artificial intelligence (AI) in healthcare and biomedical research. Recent deep research systems aim to…

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★ 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.AI2024

How Well Do Multi-modal LLMs Interpret CT Scans? An Auto-Evaluation Framework for Analyses

Qingqing Zhu, Benjamin Hou, Tejas S. Mathai +7

Automatically interpreting CT scans can ease the workload of radiologists. However, this is challenging mainly due to the scarcity of adequate datasets and reference standards for…