BACKGROUND

• Cervical cancer remains a significant global health challenge, especially in resource-limited settings with limited access to effective screening programs.
• Colposcopy is a highly sensitive method of diagnosing cervical interepithelial lesion(CIN), but it is prone to subjectivity
• Traditional screening methods face challenges in these contexts, leading to delayed diagnoses and poor patient outcomes.
• Deep learning techniques provide a promising solution by utilizing advanced algorithms to analyze colposcopy images for early detection of precancerous lesions.
• This study aimed to evaluate the use of deep learning in cervical cancer classification using precancerous images.