A Predictive Model to Detect Cervical Diseases Using Convolutional Neural Network Algorithms and Digital Colposcopy Images

Cervical diseases, specifically cervical cancer (CC), are among the leading causes of death around globe, imposing a significant challenge to scientists and healthcare providers dealing with disease patients. None existing solutions can detect various which would lead experts accurately early stages diseases due equipment limitations type medical detection tests used in those solutions. New technologies have been developed enable more rapid sensitive screening using deep learning algorithms. This study proposes predictive model (DL) algorithms colposcopy images different classes including diseases. offers sector an opportunity for early-stage diagnosis Four rounds experiments were conducted this research evaluate performance proposed model. According results, (stages) while it obtains high accuracy. The rate accuracy training stage was above 92%, highest achieved 99% third experiment. Also, round experiment, could achieve results accuracy, sensitivity values 98% 98%, respectively. Notably, last perfect specificity value 1.