
A study shows large language models can predict immunotherapy responses in liver cancer as accurately as experienced doctors.
Key Details
- 1Research led by Prof. Hai Li at Hefei Institutes systematically assessed LLMs' ability to predict liver cancer treatment response.
- 2LLMs tested: GPT-4, GPT-4o, Google Gemini, DeepSeek, and a hybrid Gemini-GPT model.
- 3Dataset included clinical and imaging data from 186 unresectable HCC patients.
- 4Gemini-GPT matched senior (15+ years) doctor accuracy and surpassed less-experienced clinicians in both speed and accuracy.
- 5Hybrid and logical strategies improved LLM performance and consistency, especially in identifying likely responders to therapy.
- 6Published in the Journal of Medical Systems on May 15, 2025.
Why It Matters

Source
EurekAlert
Related News

AI Pathology Tool SÉMIL Improves Stage II Bowel Cancer Risk Assessment
A La Trobe University-developed AI tool accurately predicts relapse risk in stage II bowel cancer using digital pathology images and descriptions.

AI Tool Predicts Which Rectal Cancer Patients Benefit from Intensive Therapy
UCL researchers developed an AI that analyzes biopsy slides to identify rectal cancer patients who benefit from adding irinotecan to standard chemoradiotherapy.

AI-Guided Handheld Cardiac Ultrasound Reduces Referrals and Costs in Spain
AI-guided handheld cardiac ultrasound enables primary care physicians to detect heart failure, reducing specialist referrals and saving costs.