J Korean Med Assoc.  2024 Nov;67(11):695-700. 10.5124/jkma.2024.67.11.695.

Applications of artificial intelligence in obstetrics

• Kim SY

• KMID: 2561741
• DOI: http://doi.org/10.5124/jkma.2024.67.11.695

Abstract

Background
Artificial intelligence (AI), particularly chatbot technologies such as OpenAI’s ChatGPT, is increasingly influencing healthcare by improving quality, efficiency, and accessibility. ChatGPT is already useful in clinical practice, research, and education across various medical fields. However, its use raises concerns regarding accuracy and reliability, and ethics. This article discusses the potential and challenges of ChatGPT application in obstetrics.
Current Concepts
In obstetrics, AI is being applied in several key areas. ChatGPT is useful for providing easy-to-understand information during unexpected birth situations and has been applied in diagnosis and patient management. Furthermore, it aids in patient education, clinical assessment, and research. In drug counseling, ChatGPT helps guide safe medication use during pregnancy and breastfeeding, although it also emphasizes consultations with healthcare professionals. AI has improved the interpretation of fetal monitoring and ultrasound accuracy and reduced the time required for diagnosis and potential errors. The recent launch of OpenAI’s “SearchGPT” could further revolutionize healthcare by providing real-time, tailored information and improving diagnostic precision.
Discussion and Conclusion
ChatGPT, although useful, has limitations such as potential misinformation and variability in responses. It can assist with patient inquiries; however, it cannot replace clinical judgment. AI holds significant promise for application in obstetrics; nevertheless, careful attention to ethical and regulatory issues, including patient privacy, is necessary. Future applications of AI may include personalized treatment plans, real-time monitoring, and the automation of administrative tasks, allowing clinicians to focus more on patient care. AI also has the potential to improve medical education, assist with complex diagnoses, and improve patient engagement and outcomes.

Keyword

Obstetrics; Artificial intelligence; Natural language processing; Deep learning; 산과; 인공지능; 자연어 처리; 딥러닝