THE ROLE OF ARTIFICIAL INTELLIGENCE IN HYSTEROSCOPY: FROM SUBJECTIVE ASSESSMENT TO OBJECTIVE DIAGNOSIS

Abstract:

Hysteroscopy is one of the key methods for diagnosing intrauterine pathology; however, interpretation of hysteroscopic findings largely depends on the clinician’s experience and image quality, which leads to diagnostic variability and an increased risk of errors. In recent years, artificial intelligence has emerged as a promising tool to enhance objectivity and reproducibility in visual diagnostics within endoscopy. This article analyzes the current state of research on the application of artificial intelligence in hysteroscopy, with an emphasis on the transition from subjective visual assessment to objective diagnosis. The main directions of artificial intelligence development in endoscopy, achieved results, and existing limitations are reviewed, along with the experience of applying similar technologies in related medical fields. Special attention is given to the current status of research in the Commonwealth of Independent States and the Republic of Uzbekistan, as well as to the opportunities arising from ongoing healthcare reforms and digitalization initiatives. The findings indicate that the integration of artificial intelligence algorithms into hysteroscopic practice has significant potential to improve diagnostic accuracy, reduce interobserver variability, and standardize the interpretation of hysteroscopic video signals, thereby justifying the need for further research in this field.