[Gynecology, Obstetrics and Fertility - Reborn in the Digital Revolution].

In recent years, artificial intelligence (AI) has brought about a dramatic transformation in obstetrics, gynecology, and fertility medicine. AI, including methods such as machine learning, deep learning, and large language models (LLMs), is reshaping the way clinical data are collected, analyzed, and applied. Image processing, particularly through deep learning applications, significantly enhances the detection of fetal anomalies in prenatal ultrasound, the classification of embryo quality in fertility treatments, and the early identification of gynecological pathologies. The integration of artificial intelligence systems with clinical expertise improves diagnostic accuracy, especially in the fields of medical imaging and pathology, while reducing the rate of false positive findings in imaging and pathology tests. However, artificial intelligence serves only as an assistive tool and does not replace medical judgment or established diagnostic standards. In parallel, machine learning models enable the prediction of pregnancy complications, the success of oncological treatments in gynecology and more. A major advantage of these models is their interpretability, which increases their potential for clinical adoption. LLMs contribute to the analysis of medical records, research summarization, and clinical decision support, although their use in other languages, such as Hebrew, remains limited. Augmented reality technologies offer new possibilities for enhancing patient experiences by reducing pain and anxiety during medical procedures. Despite the significant potential, challenges remain, including issues of data privacy and security, model reliability, and the need for appropriate regulatory frameworks. Israel, with its advanced yet heavily burdened healthcare system and high birth rates, is uniquely positioned to lead research and innovation in this field. Studying the capabilities and limitations of these tools will allow for their controlled and safe integration, promoting personalized medicine and optimizing public healthcare resource utilization. The aim of this study is to review advancements in implantation of AI tools in gynecology.