Cervical cancer prediction with Artificial Intelligence to improve the accuracy and efficiency of early detection and diagnosis of cervical cancer.
Cervical cancer is one of the most common malignancies in women, developing from precursor lesions known as cervical intraepithelial neoplasia (CIN) and through persistent infection with high-risk human papillomavirus (HR-HPV). It is a well-known cause of death for women worldwide and continues to be a significant public health concern. Early detection and treatment are essential to prevent the progression of cervical cancer and reduce its impact on women's health (2)(5).
Size of the Problem
It is essential to have accurate medical tests in the context of cervical screening and other aspects of healthcare. These tests play a fundamental role in detecting anomalies early, such as precancerous lesions, enabling timely treatment and preventing the development of invasive cancer. Additionally, by ensuring accuracy in diagnosis, these tests improve patient safety and reduce costs associated with diagnostic errors and unnecessary treatments. Therefore, improving the accuracy of medical tests not only directly impacts the quality of healthcare but can also have significant implications for reducing the global burden of cervical cancer (2)(3).