ABSTRACT
The data related to human health and medicine can be stored, searched, shared, analysed, and presented in ingenious ways and the scale of this medical big data is continuously growing with advancements in medical technology and hospital information. However, there are predicaments and problems that remain to be overcome in its current stage of inception especially on how to analyze this data in a reliable manner. In this chapter, how data mining technology is more convenient for integrating this medical data for a variety of applications such as disease diagnosis, prevention, hospital administration has been discussed. In this chapter, the practicality of big data analytics, methodological and technical issues such as data quality, inconsistency and instability, analytical and legal issues and lastly, the issue of integration of big data analytics with clinical practice and clinical utility have been analysed. It is important to overcome these challenges to secure the application of big data technology in medical field and to thus improve patient outcome and more essentially to reduce resource wastage in medical field, which should be the real aim of big data studies. This chapter also aims at exploring methods to overcome these obstacles using big data tools and understanding the potential of Hadoop, which is an open-source distributed data storage and analysis application, in managing healthcare data. An analysis and examination of possible future work for these areas is also done with a translational approach of using data from all levels of human existence.
