Prediction of precancerous cervical cancer lesions among women living with HIV on antiretroviral therapy in Uganda: a comparison of supervised machine learning algorithms

• Main Authors: Florence Namalinzi (Author), Kefas Rimamnuskeb Galadima (Author), Robinah Nalwanga (Author), Isaac Sekitoleko (Author), Leon Fidele Ruganzu Uwimbabazi (Author)
• Format: Book
• Published: BMC, 2024-07-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

Abstract Background Cervical cancer (CC) is among the most prevalent cancer types among women with the highest prevalence in low- and middle-income countries (LMICs). It is a curable disease if detected early. Machine learning (ML) techniques can aid in early detection and prediction thus reducing s...