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Current State of Artificial Intelligence Model Development in Obstetrics.

Lawrence D Devoe1, Maya Muhanna, James Maher

  • 1Department of Obstetrics and Gynecology, Medical College of Georgia at Augusta University, Augusta, Georgia; the Department of Obstetrics, Gynecology, and Reproductive Sciences, Icahn School of Medicine at Mount Sinai, and the Fetal Medicine Foundation of America, New York, New York; the Yong Loo Lin School of Medicine, National University of Singapore, Singapore; and the School of Molecular Sciences and the College of Health Solutions, Arizona State University, Phoenix, Arizona.

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Summary
This summary is machine-generated.

Artificial intelligence (AI) is rapidly advancing in obstetrics, with many studies focusing on risk prediction. While AI ultrasound shows promise, more high-quality research is needed for safe integration into U.S. obstetric care.

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Area of Science:

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

Background:

  • Publications on artificial intelligence (AI) in obstetrics have surged.
  • AI applications are being developed for various obstetric conditions.
  • Understanding current trends and future impact is crucial for obstetric practice.

Purpose of the Study:

  • Review recent AI publications in obstetrics (June 2019-May 2024).
  • Describe AI application trends for specific obstetric problems.
  • Assess the potential impact of AI on obstetric care.

Main Methods:

  • Searched multiple databases (PubMed, MEDLINE, Google Scholar, etc.) using keywords like "obstetrics," "artificial intelligence," and "machine learning."
  • Screened 1,768 articles, with 207 selected after exclusions.
  • Analyzed study characteristics, population sizes, model performance, and evidence quality.

Main Results:

  • Most AI studies in obstetrics originate outside the U.S. and focus on risk prediction.
  • AI ultrasound applications are poised to impact current obstetric care.
  • Promising AI models exist for screening preterm birth, preeclampsia, and gestational diabetes mellitus.

Conclusions:

  • AI integration into U.S. obstetric practice is likely, but current models need further validation and generalizability.
  • High-quality studies with robust predictive accuracy are essential.
  • Education for healthcare professionals on safe AI implementation is urgently required.