Utilizing ChatGPT to Facilitate Referrals for Fetal Echocardiography
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View abstract on PubMed
Summary
This summary is machine-generated.Artificial intelligence (AI) shows moderate agreement with experts in refining fetal echocardiography referrals for congenital heart defects (CHDs). AI may aid clinicians by identifying more minor CHDs, but requires clinical guidance.
Area Of Science
- Medical technology
- Artificial intelligence in healthcare
- Cardiology
Background
- Investigating the utility of OpenAI's GPT-4 as a medical decision support tool.
- Focusing on its accuracy in refining fetal echocardiography (FE) referrals for congenital heart defects (CHDs).
Purpose Of The Study
- To assess the accuracy of artificial intelligence (AI) in refining referrals for fetal echocardiography (FE).
- To compare AI's referral recommendations with those of human experts for detecting congenital heart defects (CHDs).
Main Methods
- Retrospective evaluation of 59 past FE referral cases.
- Comparison of AI recommendations against pediatric cardiologist and gynecologist (human experts) based on established guidelines.
- Analysis of agreement between AI and experts, with experts resolving discrepancies.
Main Results
- AI recommended FE in 59.0% of cases, compared to 47.5% for cardiologists and 49.2% for gynecologists.
- AI demonstrated approximately 80.0% agreement with human experts (p < 0.001).
- AI suggested more FEs for minor CHDs (64.7%) than experts (47.1%), while experts recommended FE for all major CHD cases (100%) versus AI (90.9%).
Conclusions
- Moderate agreement exists between AI and human experts in refining FE referrals.
- AI's current limitations include contextual misunderstandings and lack of specialized medical knowledge, necessitating clinical guideline integration.
- AI shows potential as a decision aid, particularly in identifying potential cases of minor CHDs.
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