Reviewing the Techniques of Disease Detection and Classification from the Challenging Medical Data

The area of healthcare sector is now meeting a new challenge of data management. Owing to adoption of advance technology for patient-related services as well as diagnosis, a high-dimensional data is being generated. The biggest problems of such data are manifold e.g. i) they are much bigger in size that is difficult to be stored in physical servers, ii) they are massively growing in size with respect to increase of time, iii) they are of various forms and formats owing to be generated from multiple devices, and iv) there is larger dimensionality of uncertainty too. Owing to all these problems, it is almost impossible to apply the conventional data analysis algorithm for extracting teh knowledge. This paper discusses about the some of the recently adopted technique for analysis such medical data for an effective disease detection and classification with a contribution of exploring the research gap for the existing literatures.