Data Analytics for Risk of Hospitalization of Cardiac Patients

Abstract

Recognizing cardiac patients with high risk of hospitalization could enable timely and life-saving care. The accumulation of healthcare data and utilization of data analytics to develop risk prediction models from healthcare data could facilitate personalized treatment care and predict the risk of emergency. Healthcare providers use different prediction tools to improve clinical decision making as there is a relation between hospitalization and disease diagnosis, disease complications and disease treatment. Several factors constitute to the hospitalization of cardiac patients such as age, gender, disease type, disease complication, associated disease conditions and so on. In this paper, a prediction model is developed to predict the risk of hospitalization of cardiac patients and the significance of each factor that contributes to the risk of hospitalization of cardiac patients is measured. The proposed model is designed to discover and validate the factors that are associated with the high risk of hospitalization in cardiac patients.

KEYWORDS:

• Cardiac risk factors
• Data analytics
• Disease diagnosis
• Healthcare
• Predictive analytics
• Prediction model
• Risk of hospitalization

Additional information

Notes on contributors

M. Chandralekha

M Chandralekha completed her PhD in the Department of Information & Communication Engineering, University College of Engineering, Bharathidasan Institute of Technology Campus, Anna University, Tiruchirappalli, Tamil Nadu, India. She obtained her bachelor's degree from Amrita Vishwa Vidyapeetham, Amrita School of Engineering, Ettimadai, Coimbatore, Tamil Nadu, India, in 2014. She received her master’s degree from PSG College of Technology, Coimbatore, Tamil Nadu, India, in 2016. She received her PhD in the year of 2020 in the research area of data mining. Her research areas include data mining, mobile computing, grid and cloud computing, information retrieval and open source systems. She has published many research articles in reputed international journals. Corresponding Author. Email: [email protected]

N. Shenbagavadivu

N Shenbagavadivu is an assistant professor in the Department of Computer Applications, University College of Engineering, Bharathidasan Institute of Technology Campus, Anna University, Tiruchirappalli, Tamil Nadu, India. She received her PhD in the year of 2011. Her research areas include distributed computing, web services, mobile and cloud computing. She has published more than 50 papers in international, national journals and conferences. She has been a reviewer for many national and international journals. Email: [email protected]