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Can large language models be new supportive tools in coronary computed tomography angiography reporting?
Eren Çamur1, Turay Cesur2, Yasin Celal Güneş3
1Department of Radiology, Ministry of Health Ankara 29 Mayis State Hospital, Ankara, Türkiye.
Clinical Imaging
|September 5, 2024
Summary
Large language models (LLMs) show strong performance in coronary artery disease (CAD) diagnosis using CAD-RADS 2.0 guidelines. ChatGPT 4o achieved 100% accuracy, highlighting LLMs' potential to improve radiological reporting and patient care.
Area of Science:
- Artificial Intelligence in Medical Imaging
- Radiology and Diagnostic Tools
- Natural Language Processing in Healthcare
Background:
- Large language models (LLMs) offer significant potential to advance natural language processing in radiology, particularly for coronary artery disease (CAD) diagnosis.
- Previous research has focused on individual LLMs, but a comparative analysis within the CAD-RADS 2.0 framework was missing.

