Can artificial intelligence-driven predictive analytics enhance maternal-fetal outcomes in midwifery? A review.
Code: G-1037
Authors: Mahdieh Joukar ℗, Shadab Shahali *
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Tag: Intelligent Virtual Assistant
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Abstract:
Abstract
Background and Aims: The integration of data and technology in healthcare enables informed decision-making, risk identification, and personalized care for expectant mothers and their infants. This review evaluates the role of AI-driven predictive analytics in assessing maternal-fetal outcomes within midwifery. Methods: Comprehensive searches were performed in Google Scholar, Web of Science, PubMed, and Scopus using relevant search terms. Eligibility was determined by screening titles, abstracts, and full texts. Data were meticulously extracted and descriptively summarized, adhering to the PRISMA guidelines. Narrative synthesis was employed for data analysis. Results: A total of 15 studies were included in this review. The extracted data were narratively categorized into four thematic groups: (1) Role of AI in Healthcare Decision-Making, (2) Applications of AI in Maternal Care, (3) Benefits such as Early Risk Identification and Prevention, and Personalized Care Plans and Interventions, and (4) Challenges and Limitations including Data Privacy and Ethical Concerns, and Integration with Existing Healthcare Systems. Conclusion: The findings underscore the transformative potential of AI in enhancing maternal care. By leveraging large datasets, AI-driven predictive analytics empower midwives to foresee and avert potential complications during pregnancy and childbirth. This technology facilitates early risk detection, allows for the customization of care plans, and ultimately improves maternal and fetal health outcomes.
Keywords
AI, Predictive Analytics, Maternal-fetal Outcomes
