Disease Prediction and Drug Recommendation Android Application using Data Mining (Virtual Doctor)
Vivek Mudaliar1, P.Savaridaasan2, Sachin Garg3

1Vivek Mudaliar, Information Technology Department, SRM Institute of Science and Technology, Kattankulathur, Chennai, (Tamil Nadu).
2P.Savaridaasan, Information Technology Department SRM Institute of Science and Technology, Kattankulathur, Chennai, (Tamil Nadu).
3Sachin Garg, Information Technology Department SRM Institute of Science and Technology, Kattankulathur, Chennai, (Tamil Nadu). 

Manuscript received on 02 August 2019. | Revised Manuscript received on 07 August 2019. | Manuscript published on 30 September 2019. | PP: 6996-7001 | Volume-8 Issue-3 September 2019 | Retrieval Number: C6038098319/2019©BEIESP | DOI: 10.35940/ijrte.C6038.098319
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© 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: Data Mining is a method that requires analyzing and exploring large blocks of data to glean meaningful trends and patterns. In today’s period, every person on earth relies on allopathic treatments and medicines. Data mining techniques can be applied to medical databases that have a vast scope of opportunity for textual as well as visual data. In medical services, there are myriad obscure data that needs to be scrutinized and data mining is the key to gain useful knowledge from these data. This paper provides an application programming interface to recommend drugs to users suffering from a particular disease which would also be diagnosed by the framework through analyzing the user’s symptoms by the means of machine learning algorithms. We utilize some insightful information here related to mining procedure to figure out most precise sickness that can be related with symptoms. The patient can without much of a stretch recognize the diseases. The patients can undoubtedly recognize the disease by simply ascribing their issues and the application interface produces what malady the user might be tainted with. The framework will demonstrate complaisant in critical situations where the patient can’t achieve a doctor’s facility or when there are situations, when professional are accessible in the territory. Predictive analysis would be performed on the disease that would result in recommending drugs to the user by taking into account various features in the database. The experimental results can also be used in further research work and for Healthcare tools.
Keywords: Data Mining Techniques, E-healthcare, Locally Frequent Patterns, Medical Data Mining, Symptoms, Drugs

Scope of the Article: Data Mining