Background: Medical informatics has observed an unrestrained growth in the database. Latest advancements in the field of medical sciences have wiped out lots of critical diseases. Nowadays, the medical industry is affluent in data sources. These data sources are of use only if these are effectively analyzed on time.

Methods: Data mining techniques are artificially intelligent and used to investigate known and unknown patterns available in the medical databases. Nowadays, data mining techniques are chronically used to mine abundant data sources of medical science. This paper explores the practice of diverse data mining techniques, the role of dataset used, effect of preprocessing, and the performances of different data mining techniques in diagnosis of different lifestyle based diseases. The venture of this paper is to fetch out stark assessments of different data mining techniques used in medical sciences.

Results: By far, surveillance discloses that significant effort has been made for mining the data allied to the Cardiology and Diabetes. As per Google Scholar, in last seven years, the percentage of articles published related to cardio, diabetes, digestive, dentistry and ophthalmology disease diagnosis using data mining are 42%, 26%, 18%, 10% and 4% respectively. So, a little attention has been paid to develop predictive model for the diseases viz. ophthalmology, dentistry and digestive disorders. In addition, the rate of usage of preprocessing in diagnosis of different disorders related to cardio, diabetes, digestive, dentistry and ophthalmology lies between 10.65%–17.75%, 8.48%–14.80%, 4.58–8.93%, 2.96%–7.73% and 5.83%–12.93% respectively.

Conclusion: An attention is obligatory to develop smart diagnostic system to aware and save human masses from wide critical spectrum of diseases related to ophthalmology, oral and digestive systems.