Assist.T.Yaqqeen Saad Ali

Cervical cancer is a significant global health concern. There are millions of deaths every year due to cancerous diseases, especially among women so there is a benefits greatly from early detection and consistent monitoring In this regard. Cancer staging is vital to the evaluation and planning of operations for women with cervical cancer. Telehealth offers a promising avenue for expanding access to care especially in remote areas. Integrating a robust cervix tumor classification system into telehealth platforms is crucial for effective remote management. Such a system, potentially leveraging AI and image analysis of colposcopies or other imaging modalities, allows remote specialists to assess and classify lesions. This facilitates timely diagnosis, treatment planning, and follow-up care, reducing the need for frequent in-person visits. Standardized classification ensures consistent communication among healthcare providers. This approach enhances patient outcomes, improves resource allocation, and contributes to more efficient cervical cancer screening programs. Cervical cancer tumor images can be classified using deep convolutional neural networks (DCNNs).