Keywords
Abstract
The integration of Artificial Intelligence (AI) into gynecology signifies a paradigm shift in women's healthcare, offering unprecedented advancements in diagnostic accuracy, therapeutic strategies, and personalized patient management. This comprehensive review delves into the multifaceted applications of AI across various gynecological domains, including reproductive medicine, oncology, benign gynecological disorders, and surgical interventions. By leveraging machine learning algorithms, deep learning models, and natural language processing, AI enhances the interpretation of complex medical data, facilitates early disease detection, and optimizes treatment planning. Notably, AI-driven tools have demonstrated superior performance in identifying conditions such as endometriosis, polycystic ovary syndrome (PCOS), and gynecologic malignancies, often surpassing traditional diagnostic methods. Furthermore, the incorporation of AI in assisted reproductive technologies (ART) has improved embryo selection processes, thereby increasing success rates. Despite these advancements, challenges persist, including data privacy concerns, algorithmic biases, and the need for extensive, diverse datasets to train robust AI models. Addressing these issues through interdisciplinary collaboration and ethical frameworks is imperative to fully realize AI's potential in gynecology. This review underscores the transformative impact of AI, advocating for its continued integration to enhance patient outcomes and revolutionize gynecological care.
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