
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 and Advanced Microscopy Unveil Cell's Exocytosis Nanomachine
Researchers have discovered the ExHOS nanomachine responsible for constitutive exocytosis using advanced microscopy and AI-enhanced image analysis.

Physical Activity Linked to Breast Tissue Biomarkers in Teens
A study links adolescent recreational physical activity to changes in breast tissue composition and stress biomarkers, potentially impacting future breast cancer risk.

AI Reveals Key Health System Levers for Cancer Outcomes Globally
AI-based analysis identifies the most impactful policy and resource factors for improving cancer survival across 185 countries.