GPT-4o, with prompt engineering, selected optimal abdominal/pelvic CT protocols more accurately than radiologists without increasing inappropriate selections.
Key Details
- 1Study evaluated 1,448 abdominal and pelvic CT exams between Jan-June 2024.
- 2GPT-4o with detailed prompting selected optimal protocols 96.2% of the time, compared to 88.3% for radiologists (p<0.001).
- 3Rates of inappropriate protocols were similarly low: 1.3% (GPT-4o) vs. 2.4% (radiologists), not statistically significant (p=0.21).
- 4Fine-tuning GPT-4o offered no performance increase over meticulous prompting (both 96.2%).
- 5Performance in protocol matching was consistent across training levels (radiologist, fellow, resident).
Why It Matters
Automating protocol assignment with LLMs like GPT-4o could streamline imaging workflow, freeing radiologists for more complex tasks and reducing the risk of workflow interruptions and diagnostic errors. The approach may allow for adaptable, institution-specific automation without intensive retraining.
Source
AuntMinnie
Related News
•Radiology Business
AI-Powered Tool Streamlines CT Scan Prioritization in Emergency Departments
An AI-based CT queue system significantly reduces wait times for ED patients by prioritizing scans likely to reveal critical findings.
•Radiology Business
AI Workflow Enables General Radiologists to Match Breast Specialists in Screening
AI-powered workflow helps generalist radiologists detect breast cancer at rates comparable to specialists.
•Radiology Business
LLMs Automate Radiology Report Quality Control, Study Finds
LLM-based systems can rapidly automate radiology report quality control, saving significant manual review time.