• Gaurav Bagade
• Ninad Bhate
• Sarika Pawar
• Pratik Sonawane
• Pratik Sonawane

In our society, humans pay more attention to their own fitness. Personalized fitness service is regularly rising. Due to lack of skilled doctors and physicians, maximum healthcare corporations cannot meet the clinical call of public. Public want extra accurate and on the spot result. Thus, increasingly more facts mining packages are evolved to provide humans extra custom designed healthcare provider. It is a good answer for the mismatch of insufficient clinical assets and growing medical demands. Here an AI-assisted prediction device is advocated which leverages information mining strategies to show the relationship between the everyday physical examination information and the capability fitness danger given through the consumer or public. The main concept is to decide clinical illnesses in step with given signs and symptoms & every day Routine where user search the sanatorium then given the closest medical institution of their cutting-edge area. The machine gives a user-friendly interface for examinees and medical doctors. Examinees can recognize their symptoms which amassed in frame which is set at the same time as medical doctors can get a fixed number of examinees with capacity.

Data mining, machine learning and disease prediction

"A SURVEY ON EVOLTIONARY ALGORITHMS FOR HEALTH RISK PREDICTION ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.14-19, May-2019, Available :http://www.jetir.org/papers/JETIR1905M04.pdf

"A SURVEY ON EVOLTIONARY ALGORITHMS FOR HEALTH RISK PREDICTION ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp14-19, May-2019, Available at : http://www.jetir.org/papers/JETIR1905M04.pdf