
Researchers developed an AI tool using natural language processing to accurately identify primary cancer types in patients with brain metastases by analyzing clinical notes.
Key Details
- 1MUSC Hollings Cancer Center team created an NLP model for electronic health records (EHR) notes.
- 2The tool correctly identified the primary cancer in over 90% of cases (97% for common types).
- 3It outperformed standard ICD codes, which often lack specificity for cancer origins and subtypes.
- 4The study analyzed 82,000 clinical notes from more than 1,400 stereotactic radiosurgery patients.
- 5The approach is lightweight, scalable, and requires relatively little data or computing power.
- 6The model can improve research and treatment planning for patients undergoing targeted brain radiation.
Why It Matters

Source
EurekAlert
Related News

Chinese Researchers Unveil Photonic Chip for Ultra-Fast Image Processing
A new photonic chip achieves image processing at 25 million frames per second with high energy efficiency, promising major advances in real-time imaging and AI applications.

AI Model Predicts Growth Spurts from Pediatric Neck X-rays for Orthodontics
Korean researchers developed an AI system (ARNet-v2) that predicts children's growth spurts from neck X-rays to enhance orthodontic treatment planning.

Dana-Farber Showcases AI and Clinical Trial Advances at ESMO 2025
Dana-Farber researchers present major cancer clinical trial results, including AI-driven data analysis, at ESMO Congress 2025.