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- Title
Exploring the potential of machine learning in gynecological care: a review.
- Authors
Khan, Imran; Khare, Brajesh Kumar
- Abstract
Gynecological health remains a critical aspect of women's overall well-being, with profound implications for maternal and reproductive outcomes. This comprehensive review synthesizes the current state of knowledge on four pivotal aspects of gynecological health: preterm birth, breast cancer and cervical cancer and infertility treatment. Machine learning (ML) has emerged as a transformative technology with the potential to revolutionize gynecology and women's healthcare. The subsets of AI, namely, machine learning (ML) and deep learning (DL) methods, have aided in detecting complex patterns from huge datasets and using such patterns in making predictions. This paper investigates how machine learning (ML) algorithms are employed in the field of gynecology to tackle crucial issues pertaining to women's health. This paper also investigates the integration of ultrasound technology with artificial intelligence (AI) during the initial, intermediate, and final stages of pregnancy. Additionally, it delves into the diverse applications of AI throughout each trimester. This review paper provides an overview of machine learning (ML) models, introduces natural language processing (NLP) concepts, including ChatGPT, and discusses the clinical applications of artificial intelligence (AI) in gynecology. Additionally, the paper outlines the challenges in utilizing machine learning within the field of gynecology.
- Subjects
MACHINE learning; NATURAL language processing; ARTIFICIAL intelligence; DEEP learning; PATTERNMAKING; SPERM banks; ADOLESCENT gynecology
- Publication
Archives of Gynecology & Obstetrics, 2024, Vol 309, Issue 6, p2347
- ISSN
0932-0067
- Publication type
Article
- DOI
10.1007/s00404-024-07479-1