DISEASE PREDICTION HEALTHCARE RECOMMENDATION SYSTEM USING DATAMINING
| Author(s) | : | Dr. Riyazoddin Siddiqui, Neyazi Danish, Khokhar Mustafa |
| Institution | : | Associate Professor, Department of I.T, MHSS College of Engineering, Mumbai, India |
| Published In | : | Vol. 5, Issue 5 — May 2018 |
| Page No. | : | 96-98 |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
In today's era, it might have happened so many times that you or someone of yours needs doctors assistanceimmediately, but they are not available to reach it on time due to some reason. The Smart Healthcare Recommendationsystem is an end user support and online consultation project. Here we propose a system through an intelligent diseasesystem online. The system is fed with various symptoms and the disease/illness associated with those systems. The systemallows user to share their symptoms. It then processes users symptoms to check for various disease that could beassociated with it. Here we use some intelligent data mining techniques to guess the most accurate disease that allowsusers to get instant guidance on their health issues that could be associated with patient’s symptoms. If the system is notable to provide suitable results, it informs the user about the type of disease or disorder it feels user’s symptoms areassociated with. If users symptoms do not exactly match any disease in our database, is shows the diseases user couldprobably have judging by his/her symptoms. It also recommends medicines for disease predicted to the user dependingupon symptoms received .The system also provides details about medical stores surrounding current location of the user,which may help user to get medicines as soon as possible in emergency.
Dr. Riyazoddin Siddiqui, Neyazi Danish, Khokhar Mustafa, “DISEASE PREDICTION HEALTHCARE RECOMMENDATION SYSTEM USING DATAMINING”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 5, Issue 5, pp. 96-98, May 2018.








