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
This work demonstrates the emerging capability of LLMs to support and enhance personalized cancer treatment decisions, showing they can complement or even match the expertise of experienced radiologists and oncologists in outcome prediction.
Source
EurekAlert
Related News
•EurekAlert
MD Anderson Unveils New AI Genomics Insights and Therapeutic Advances
MD Anderson reports breakthroughs in cancer therapeutics and provides critical insights into AI models for genomic analysis.
•EurekAlert
UCLA Researchers Present AI, Blood Biomarker Advances at SABCS 2025
UCLA Health researchers unveil major advances in breast cancer AI pathology, liquid biopsy, and biomarker strategies at the 2025 SABCS.
•EurekAlert
SH17 Dataset Boosts AI Detection of PPE for Worker Safety
University of Windsor researchers released SH17, a 8,099-image open dataset for AI-driven detection of personal protective equipment (PPE) in manufacturing settings.