Advancing Obstetric Care Through Artificial Intelligence-Enhanced Clinical Decision Support Systems: A Systematic...

Area of Science:

• Obstetrics and Gynecology
• Medical Informatics
• Artificial Intelligence in Healthcare

Background:

• Clinical Decision Support Systems (CDSS) are increasingly used in obstetrics.
• The specific functions and AI techniques within AI-augmented CDSS for obstetrics remain underexplored.

Purpose of the Study:

• To systematically review and synthesize the functionality, AI techniques, and clinical implementation of AI-augmented CDSS in obstetric care.

Main Methods:

• A systematic review was conducted searching four databases (Scopus, PubMed, Web of Science, IEEE Xplore).
• 354 studies were initially identified, with 30 included after eligibility assessment.
• Risk of bias was assessed using the Newcastle Ottawa Scale.

Main Results:

• Key CDSS functionalities include medical prediction, therapeutic recommendations, diagnostic support, and knowledge dissemination.
• AI applications identified encompass early fetal anomaly detection, economical surveillance, and prenatal ultrasonography assistance.
• Ontology development methodologies were also noted in the reviewed literature.

Conclusions:

• AI-augmented CDSS offer diverse functionalities in obstetrics, including advanced diagnostic and predictive capabilities.
• Further research is needed to fully understand and optimize the integration of AI techniques into obstetric CDSS.