Diagnosis of Cervical Cancer and Pre-Cancerous Lesions by Artificial Intelligence: A Systematic Review
- Autori: Allahqoli, Leila; Laganà , Antonio Simone; Mazidimoradi, Afrooz; Salehiniya, Hamid; Günther, Veronika; Chiantera, Vito; Karimi Goghari, Shirin; Ghiasvand, Mohammad Matin; Rahmani, Azam; Momenimovahed, Zohre; Alkatout, Ibrahim
- Anno di pubblicazione: 2022
- Tipologia: Articolo in rivista
- OA Link: http://hdl.handle.net/10447/574646
Abstract
The likelihood of timely treatment for cervical cancer increases with timely detection of abnormal cervical cells. Automated methods of detecting abnormal cervical cells were established because manual identification requires skilled pathologists and is time consuming and prone to error. The purpose of this systematic review is to evaluate the diagnostic performance of artificial intelligence (AI) technologies for the prediction, screening, and diagnosis of cervical cancer and pre-cancerous lesions.