Actualización en ginecooncología desde la inteligencia artificial: ¿Qué evidencia tenemos disponible?

Resumen

Abstract: Artificial intelligence is a promising tool that is transforming gynaecological oncology by bringing about improvements in early detection, image interpretation, digital pathology, prognostic assessment and personalised treatment for cervical, ovarian
and endometrial cancer. This narrative review brings together evidence on the clinical use of computational models applied to screening, diagnostic classification, radiomics, therapeutic decision support and recurrence surveillance. According to the
evidence, studies reveal promising performance across multiple scenarios, particularly when these technologies are integrated with clinical, histopathological, molecular and imaging data. However, their implementation presents significant limitations, such as
methodological heterogeneity, limited external validation, the risk of algorithmic bias, and ethical challenges related to transparency, privacy and clinical applicability. Despite this, artificial intelligence represents a significant opportunity to strengthen precision medicine in gynaecological cancer and optimise diagnostic and therapeutic processes, provided that its incorporation is accompanied by rigorous validation, specialist oversight and appropriate regulatory frameworks.

Keywords: "Genital Neoplasms, Female"; "Artificial Intelligence"; "Machine Learning"; "Diagnostic Imaging"; "Precision Medicine" (MeSH/DeCS)