ARTIFICIAL INTELLIGENCE-BASED DIAGNOSTIC CAPABILITIES IN OBSTETRICS AND GYNECOLOGY: A COMPREHENSIVE REVIEW
DOI:
https://doi.org/10.55640/Keywords:
Artificial Intelligence; Machine Learning; Obstetrics; Gynecology; Diagnostic Imaging; Prenatal ScreeningAbstract
Artificial intelligence (AI) has emerged as a transformative technology in obstetrics and gynecology, offering enhanced diagnostic accuracy through machine learning and deep learning algorithms. To systematically review AI-based diagnostic tools in obstetrics and gynecology and evaluate their clinical performance. Comprehensive literature review of studies published 2018-2025 using PubMed, Scopus, and Web of Science databases. Analysis of 147 studies revealed AI applications in prenatal screening (sensitivity 91-98%), cervical cancer screening (accuracy 89-96%), ovarian tumor classification (AUC 0.87-0.94), and pregnancy outcome prediction (precision 82-91%). AI-based diagnostic tools show substantial promise but require rigorous clinical validation, bias mitigation, and workflow integration before widespread implementation.Downloads
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