A Novel Approach on Machine Learning based Data Warehousing for Intelligent Healthcare Services

Abstract

Data warehouse is an intelligent data management system which can play vital role in digital healthcare system. In a healthcare system, we experience with a variety of challenging issues such as medical data storing, complex-data modeling, sophisticated categorization of diverse structures, and integration of extremely complicated data. To address the above problems, data warehouse can ease our decision making process effectively. In this paper, we first analyse the current statuses of the data warehousing in the digital healthcare systems. Later, we find gaps of different approaches and propose a novel machine learning based techniques to combat with the challenging issues by using data warehouse in the domain of healthcare systems. We extract data of different formats, i.e., structured, unstructured, semi-structured, image and pathological data. After extracting, transforming and loading (ETL) stages, we systematically select data by using machine leaning techniques for further decision making process. Our approach shows a novel and intelligent technique to build an operable environment for data warehouse in health care domain.