A Review of Semantic Annotation Models for Analysis of Healthcare Data Based on Data Mining Techniques

Abstract

The evolution of medial data has made interaction and communication between devices very important and need of the hour to address the problems and requirements of the people in the medical domain. It seems to be an important task to overcome the compatibility issues between the communicating devices in the healthcare sector and provide meaningful solutions to the users of medical data. In the present era, interconnection of various sensors and devices in the medical domain is possible to a great extent with the advent of Internet. In the field of medicine, the major problems, viz. interoperability of heterogeneous medical devices, security of the patient information, and personalized visualization of the processed data seems to be very vital. This paper presents an analysis of the different data mining techniques applied in healthcare domain and semantic annotation of healthcare data for overcoming the issue of interoperability. The paper also discusses about the proposed research work which includes creating a semantic model for handling heterogeneous healthcare data and the application of feature selection algorithms and classification algorithms for medical diagnosis.