A Systematic Review of Midwifery Practices and AI Integration in Maternal and Obstetric Healthcare: A Comparative Analysis
DOI:
https://doi.org/10.64149/J.Carcinog.24.5s.1207-1220Keywords:
Midwifery, Artificial Intelligence, Maternal Healthcare, AI in Obstetrics, Midwives’ Perceptions, AI Education, AI Clinical Applications, Egypt, Saudi ArabiaAbstract
Background: Although its use in midwifery varies across the medical field, artificial intelligence (AI) is increasingly being incorporated into maternal and obstetric care. To examine midwifery practices and AI integration in Saudi Arabia and Egypt, this systematic review examined variations in midwives' perspectives, clinical applications, and educational attainment.
Methods: According to PRISMA criteria, a systematic review was carried out using articles acquired from PubMed, Scopus, Web of Science, CINAHL, and Google Scholar. The review included AI midwifery educational and practical articles published between 2022 and 2024 in Egypt and Saudi Arabia. AI-driven diagnostic investigations were evaluated using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2), whereas quasi-experimental investigations were evaluated using the Critical Appraisal Skills Programme (CASP) Checklist.
Results: Six research investigations from two countries were considered in the systematic review; three have been released in Saudi Arabia and three in Egypt between 2022 and 2024. The primary purpose of AI implementation in Egypt was education; standardized training programs significantly improved midwives' attitudes and knowledge of AI (p < 0.000). Saudi Arabia, on the other hand, has placed a strong emphasis on clinical AI applications, such as E-Partographs and predictive AI algorithms, which have improved the accuracy of stillbirth predictions and labor management. Insufficient awareness and training were obstacles to the widespread implementation of AI in Egypt, while issues with data privacy and workflow adaptation were identified in Saudi Arabia. Saudi Arabia's outstanding AI tools and supportive regulations, as well as Egypt's organised AI education programs, served as facilitators.
Conclusion: To improve maternal healthcare outcomes, the study suggests increasing AI education in Egypt and refining
AI clinical applications in Saudi Arabia. To optimise AI's influence on midwifery practice, future studies should focus on ethical issues, real-world AI assurance, and the integration of AI with electronic health records (EHRs).
