A Web-Based Expert System for Diagnosing Cervical Cancer Using Dempster-Shafer Method

Cervical cancer is classified among the diverse array of cancer types that have been identified, primarily attributed to the infection of Human Papillomavirus (HPV). Cervical cancer is a form of cancer that can be effectively prevented. However, patients frequently initiate treatment after the cancer has metastasized and progressed to an advanced stage, rendering it challenging to manage and contributing to its elevated mortality rate. Therefore, a cervical cancer diagnostic expert system has been developed utilizing the Dempster-Shafer method on the web. This system aims to facilitate the early detection of cervical cancer by analyzing symptoms and risk factors. The findings of this study demonstrate the successful development of an expert system application that utilizes the Dempster-Shafer method to generate results. The application achieved a high level of accuracy, specifically 93.34 %, as determined by the diagnosis conducted by an expert specializing in cervical cancer. The application also collects user satisfaction data, which reveals an average score of 89.50% based on the End-User Computing Satisfaction (EUCS) method. This indicates a high level of satisfaction among the majority of users when utilizing the application.