An Analytical Review on Application of Deep Learning in Medical Big Data Analysis

Abstract

The data of medical health has also incremented dramatically and methods of interpreting medical-driven huge big data have originated as the requirement with time, assisting in the reorganization of medical health condition intelligently the with the use of technologies of computer widely. Due to the heterogeneous, noisy, and unstructured nature of medical big data, it is still a difficult task to analyze medical big data. The conventional methods of machine learning can’t find out the major information involved in the medical big data efficiently, while deep learning designs a hierarchical model. It consists of effective features of extraction, potential feature expression, and typical model construction. This paper is dedicated to surveying different approaches for medical big data processing using a deep learning approach and extracting finding for future research scope