Hospital supervision or healthcare administration requires management, leadership, and the administration of hospital healthcare systems and hospital networks. Healthcare systems these days generate vast amounts of complicated information concerning patients, medical devices, electronic patient records and sickness designation, and hospital resources. The vast amount of data and information could be a significant source for interpreting and evaluating knowledge that helps to reduce costs and improve cognitive processes. Data mining is a set of techniques and methods to extend the present data in order to offer new or relevant insights and expertise to healthcare practitioners for improved decision-making. In the healthcare industry, big data consists of electronic health datasets or flat-file data which are disordered, complex, and so large that they are nearly impossible to manage with the available tools or traditional hardware and software techniques. For the healthcare data/information, there is a very large amount of data available for understanding the patterns and trends; hence, big data analytics has the potential to improve healthcare services and provide cost reductions. This chapter explores data mining applications, challenges and some future directions for health care. In particular, it discusses data mining and its applications within the major areas of healthcare. This hospital-based survey also explores the utility of various data mining techniques, such as association rule, clustering, and classification in the healthcare domain. This chapter also defines the cancer site and the morphology patterns among various patients with cancer with the help of above-defined data mining techniques.
Authors: Pankaj Dadheech, Ankit Kumar, Sanwta Ram Dogiwal, Vipin Jain, Vijander Singh, Linesh Raja
DOI: https://doi.org/10.1201/9781003121152-12
Publish Year: 2021
