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Abstract

Cervical cancer remains a significant global health challenge, with early detection playing a pivotal role in improving patient outcomes. Artificial intelligence (AI) has emerged as a promising tool to enhance the accuracy and efficiency of cervical cancer diagnosis. This article provides an overview of the role of AI in cervical cancer diagnosis, focusing on its applications in image analysis, molecular diagnostics, and risk prediction. By leveraging machine learning algorithms and deep learning techniques, AI systems can analyze Pap smear images, liquid biopsy data, and patient risk factors with unprecedented speed and precision. The integration of AI into cervical cancer screening and surveillance holds the potential to standardize interpretation, reduce variability, and optimize resource allocation, ultimately leading to earlier detection and intervention. However, challenges such as data privacy, algorithm bias, and regulatory considerations must be addressed to ensure the successful implementation of AI in clinical practice