Paper Title
Artificial Intelligence for Cervical Cancer Prediction and Detection in Imaging Data - An Insight

Abstract
World Health Organization (WHO) recognizes Cervical cancer (Cc) as a significant contributor to global death rates. The precise and timely evaluation of Cervical Cancer risk is critical for effective cervical cancer management and the reduction of associated morbidity. The study explores recent advancements in leveraging artificial intelligence (AI) that explicitly detect and predict Cervical cancer. It delves into the diverse modalities of AI, including Machine Learning (ML) and Deep learning (DL) employed in analysing medical imaging data associated with Cervical Cancer. It further compares the current models developed for cervical cancer diagnosis. It highlights their strengths, limitations, and potential implications for medical practice. The paper outlines potential future directions in AI-driven cervical cancer research, including multi-modal data integration, datasets containing longitudinal data and mechanisms for dynamic dataset updating in healthcare. Keywords - Cervical cancer (Cc), Artificial Intelligence (AI), Deep Learning (DL), Machine Learning (ML), Detection, Prediction, Screening.