Predictive modeling and web-based tool for cervical cancer risk assessment: A comparative study of machine learning models.

In today's digital era, the rapid growth of databases presents significant challenges in data management. In order to address this, we have developed and designed CHAMP (Cervical Health Assessment using machine learning for Prediction), which is a user interface tool that can effectively and efficiently handle cervical cancer databases to detect patterns for future prediction diagnosis. CHAMP employs various machine learning algorithms which include XGBoost, SVM, Naive Bayes, AdaBoost, Decision Tree, and K-Nearest Neighbors in order to predict cervical cancer accurately.