Cancer prediction system: Cancer Vision

• Main Authors: Sehrish, Kantroo, Sumbula, Tahmida Haque, Abd Rahim, Noor Hayani
• Format: Book Chapter
• Language: English
• Published: Universiti Kuala Lumpur Publishing 2022
• Subjects: T58.5 Information technology
• Online Access: http://irep.iium.edu.my/110669/1/110669_Cancer%20prediction%20system.pdf; http://irep.iium.edu.my/110669/; https://icpex.unikl.edu.my/result-e-book/
• Institution: Universiti Islam Antarabangsa Malaysia

This project involves evaluating and designing a cancer prediction system to assist people who are health-conscious and suspect they are experiencing cancer symptoms. The main goal of this project is to assist users in predicting cancer early on before it progresses to a life-threatening level. Cancer Vision gives information about various cancer types that every user should be aware of. This system will predict cancer when users will input their symptoms and on the basis of those symptoms, the system will apply the decision tree technique i.e, it will run the results based on decisions by checking the answers of the user. Cancer Vision's results will display whether the user has a probability of getting cancer, the type of cancer, the status (positive or negative), and a test recommendation. In addition, if the user requires consultation or information on hospitals and doctors, this system can help. Visual studio code, laravel, and js node are being used to develop this system.