3.5k citations · 3.7k across the 10 of their papers we have counts for
4 papers · 1 filter
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…
Shadow and Light: Digitally Reconstructed Radiographs for Disease Classification
Benjamin Hou, Qingqing Zhu, Tejas Sudarshan Mathai +3
In this paper, we introduce DRR-RATE, a large-scale synthetic chest X-ray dataset derived from the recently released CT-RATE dataset. DRR-RATE comprises of 50,188 frontal Digitally…
Leveraging Professional Radiologists' Expertise to Enhance LLMs' Evaluation for Radiology Reports
Qingqing Zhu, Xiuying Chen, Qiao Jin +6
In radiology, Artificial Intelligence (AI) has significantly advanced report generation, but automatic evaluation of these AI-produced reports remains challenging. Current metrics,…
Hidden flaws behind expert-level accuracy of multimodal GPT-4 vision in medicine
Qiao Jin, Fangyuan Chen, Yiliang Zhou +15
Recent studies indicate that Generative Pre-trained Transformer 4 with Vision (GPT-4V) outperforms human physicians in medical challenge tasks. However, these evaluations primarily…