Multi-Criterial Based Feature Selection for Health Care System

Abstract

Health is the basis of a happy and successful living, and modern people have significantly benefited from medical advancements. More information is available to analyze the difficulties that affect our well-being with each new technology. Researchers may be able to answer previously inaccessible health problems due to analyzing and sequencing health data. Data in health care system is rapidly rising due to information of data analyzed with the help of IoT medical devices, availability of data in clinics and health care facility centers and with various Electronic Health Records (EHRs). Healthcare is a significant sector that deals with a variety of multi-objective and many-objective dilemmas. Quantum computing addresses specific objectives within an ideal timeframe by simultaneously working on numerous features and distinct processes. The proposed technique is a multi-criteria-based quantum health feature selection system for offering the optimum health care facilities to patients in the healthcare sector. The features are grouped into various criteria based on their applicability during a literature assessment. With the help of the Entropy technique, weight has been allocated to these selected features. To evaluate these features, the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) strategy was adopted, in which the features were ranked to find the most suitable features among a group of features. This mechanism employs methods for weighting criteria and evaluating the most appropriate quantum features to be used by the healthcare industry and practitioners in improving patient care in health facility units.