Review of Data Analytic Techniques for Health Data

Recent years have experienced a tremendous explosion in digital healthcare data. The field of data analytics has also emerged with advance technologies of machine learning and deep learning. It has boosted the data driven medical research based on data analytics. Deep learning has gained importance in the field of machine learning due to its techniques of feature representation and pattern recognition. Health data is obtained in various forms, from varied sources, contexts, technologies, and their nature can affect the proper analysis. These variations and differentiations needs to be managed for meaningful analysis.. Such health data needs aggregation and integration for the effective application of data analytic techniques. In this review we survey the challenges in data analytics, sources, types of medical data and the techniques that can be applied for the effective diagnosis. Various machine learning techniques and deep learning models are also reviewed for their effective and efficient application in the health care domain.