SYMPTOMS BASED DISEASE PREDICTOR First Step Towards Healing

Veronica Naosekpam

Data mining, data science, disease, symptoms, prediction, decision making, tree maps

Day by day, in the field of medical science, there is a rise of lot of diseases in the world. It is difficult to analyse all kind of diseases and how to take the correct medication for all the diseases. This task is very difficult. The healthcare industry collects huge amount of data which are not mined unfortunately. If these data are mined, they will be helpful to discover hidden information for effective decision making. The data mining techniques are very useful for finding the medicinal decision for the appropriate diseases. Data mining applications in healthcare can have tremendous potential and usefulness. Discovery of hidden patterns and relationships often goes unexploited. Advanced data mining techniques can help remedy this situation. Data Mining is used to discover knowledge out of data and presenting it in a form that is easily understand to humans. It is a process to examine large amounts of data routinely collected. Data mining is most useful in an exploratory analysis because of nontrivial information in large volumes of data. It is a cooperative effort of humans and computers. Best results are achieved by balancing the knowledge of human experts in describing problems and goals with the search capabilities of computers. The motivation behind the project is to facilitate medical solicitation at the earliest stage to the user and providing free of cost system of diagnosis. Correct diagnosis is critical for effective treatment and of disease. Quality of service provided to the patients could be increased by eliminating unwanted bias, errors and excessive medical costs.

Volume 5 Issue 4, October-2017

Pages : 640-643