Digitization of Gynecology Using Artificial Intelligence: Cervical Mapping Corroborated With Clinical Data for Conization Necessity

Abstract

Cervical cancer is the fourth most common female malignancy worldwide. In developing countries, it is the most common subtype of cancer and the third leading cause of cancer mortality among women. Artificial intelligence has the potential to be of real use in the prevention and prompt diagnosis of cervical cancer. The aim of our study was to develop a medical platform consisting of an automated observation sheet containing colposcopy data, a software that would use a machine learning module based on clinical and image data for diagnosis and treatment, and a telemedicine module to enable collaboration between gynecologists.

Keywords

• cervical cancer
• colposcopy
• human papilloma virus
• machine learning
• artificial intelligence