Detection of Cancer Using Boosting Tech Web App
Mareedu Girish, Madasu Satish, Thota Hemanth · International Journal for Research in Applied Science and Engineering Technology · 2023
bstract: The early detection and prognosis of a cancer type have turned into a major requirement, as it facilitates successive medical treatment of patients. The machine learning field has shown greater potential in applications such as disease prediction and drug response prediction. Input is obtained in the form of an image for cancer prediction. Output results are acquired instantly in real time. We will be using CNN methodology. The existing systems are simple and effective but are extremely vulnerable to impact. Moreover, state-of-the-art methods work on just one algorithm which makes it less accurate and more time-consuming. We propose an end-end web application that predicts cancer using distinct techniques related to deep learning... The Advantages of the proposed system are that it could be the very first-of-its-kind, cost efficient, and highly accurate application that provides complete and accurate cancer prediction. The proposed application is highly applicable in the classification, and diagnosis of cancer and tumor diseases and is expected to become more important in medical practice shortly