Prospective Applications of Artificial Intelligence In Fetal Medicine: A Scoping Review of Recent Updates
- PMID: 39834911
- PMCID: PMC11745059
- DOI: 10.2147/IJGM.S490261
Prospective Applications of Artificial Intelligence In Fetal Medicine: A Scoping Review of Recent Updates
Abstract
Introduction: With the incorporation of artificial intelligence (AI), significant advancements have occurred in the field of fetal medicine, holding the potential to transform prenatal care and diagnostics, promising to revolutionize prenatal care and diagnostics. This scoping review aims to explore the recent updates in the prospective application of AI in fetal medicine, evaluating its current uses, potential benefits, and limitations.
Methods: Compiling literature concerning the utilization of AI in fetal medicine does not appear to modify the subject or provide an exhaustive exploration of electronic databases. Relevant studies, reviews, and articles published in recent years were incorporated to ensure up-to-date data. The selected works were analyzed for common themes, AI methodologies applied, and the scope of AI's integration into fetal medicine practice.
Results: The review identified several key areas where AI applications are making strides in fetal medicine, including prenatal screening, diagnosis of congenital anomalies, and predicting pregnancy complications. AI-driven algorithms have been developed to analyze complex fetal ultrasound data, enhancing image quality and interpretative accuracy. The integration of AI in fetal monitoring has also been explored, with systems designed to identify patterns indicative of fetal distress. Despite these advancements, challenges related to the ethical use of AI, data privacy, and the need for extensive validation of AI tools in diverse populations were noted.
Conclusion: The potential benefits of AI in fetal medicine are immense, offering a brighter future for our field. AI equips us with tools for enhanced diagnosis, monitoring, and prognostic capabilities, promising to revolutionize the way we approach prenatal care and diagnostics. This optimistic outlook underscores the need for further research and interdisciplinary partnerships to fully leverage AI's potential in driving forward the practice of fetal medicine.
Keywords: Bisha; Saudi Arabia; artificial intelligence; fetal medicine; fetal monitoring; machine learning; prenatal care.
© 2025 Miskeen et al.
Conflict of interest statement
The authors report no conflicts of interest in this work.
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