An Instant Guidance on Cancer Prediction and Care Using Web Application
K.Malarvizhi1, G.Rajivsureshkumar2
1K. Malarvizhi, Associate Professor, Department of Computer Science and Engineering, JCT College of Engineering and Technology, Tamil Nadu in India.
2G. Rajivsureshkumar, Professor, Department of Computer Science and Engineering, JCT College of Engineering and Technology, Tamil Nadu in India.
Manuscript received on 04 April 2019 | Revised Manuscript received on 11 April 2019 | Manuscript Published on 26 April 2019 | PP: 225-228 | Volume-8 Issue-6S April 2019 | Retrieval Number: F60600486S19/19©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The medical field comprises heterogeneous data such as text, facts and images that can be properly separated to provide useful medical information. The medical data has been useful to the doctor in order to identify the pattern of disease. The predicted endurance of the patient after the illness is complex to sternness of the disease. The main goal of this paper is to design the web application for cancer prediction. There are various techniques used earlier for predicting the cancer disease. Cancer is one of the primary causes of demise in global. In the existing system have ensued several times require doctors assist immediately, but they are not accessible owing to a few reasons. The proposed system is an instant guidance on cancer prediction and care is developed for end users to sustain online session project. A web application is designed for users to acquire through control on their cancer disease using an online intelligent system. This application provides variety of cancer related information. The system facilitates users to determine their cancer related issues. It also directs the user precise details to ensure for the range of illnesses that could be linked with it. Data mining techniques are used to deduce the perfect level of disease that could be connected with patient’s details. We have verified the outcome for classification routinely shows the specific doctor’s place and status. A reservation system is ruined where users can honestly reserve their doctors for promote cure. A response system is as long as useful where users can allocate and view comment and status of doctors and hospitals.
Keywords: Decision Tree, K-Means, Cancer Prediction, Prognosis, Risk Levels, reservation and Response System.
Scope of the Article: Computer Science and Its Applications