Predictive Model to Identify Higher Risk of Cervical Cancer
Mangali Sunil, Neha Bollampally, Patnam Sakshit
Department of Information Technology
Malla Reddy College Of Engineering & Technology
Hyderabad, India.
Abstract
Cervical cancer is a malignancy that affects the cervix. Cervical cancer typically develops slowly over several years, progressing through precancerous changes in the cells of the cervix before becoming invasive cancer. In the relentless pursuit of enhancing healthcare outcomes, this cervical cancer risk prediction project aims to develop an innovative model that empowers both healthcare professionals and patients with proactive insights. Cervical cancer remains a significant global health challenge, but with the fusion of innovative technology and medical expertise, we strive to create a solution that can identify and communicate risk factors accurately. The main goal of this project is to create a model that, in addition to identifying risk indicators, also converts this information into useful insights. We set out on our journey by carefully undertaking system analysis, design, and implementation, and we coordinate our efforts with the accuracy of medical knowledge and the scalability of machine learning techniques. This documentation embodies our dedication to data privacy and serves as a comprehensive roadmap from conceptualization to deployment. The highest care and responsibility are used when handling patient information to maintain their trust. At the heart of this project lies the ability to provide understandable and accessible risk predictions. The system's output gives an accurate cervical cancer risk prediction and a deeper understanding of their health for proactive measures. Our objective is to provide a tool that not predicts the likelihood of cervical cancer but also instills trust, in users and the medical community through rigorous testing and validation. As we document this research, we envision a future where early detection and prevention serve as strategies, in combating cancer resulting in improved quality of life and medical outcomes.
