A Novel Enhanced Krill Herd Optimization Based Quality Prediction for Health Care Services

Some patients with a recent diagnosis of coronary heart disease report drastic drops in their health-related quality of life (HRQoL). Factors predicting HRQoL in patients with an acute coronary syndrome diagnosis were the subject of scant prior research. Quality of life is not conceived of as a risk factor for cardiovascular disease (CVD), despite the fact that there are robust associations between self-reported health and mortality. Our goal was to examine whether or not HRQoL was a separate predictor of incident CVD. It further aims at integrating the Data Analytics to enhance the quality of healthcare services such as heart disease examination. In this paper, we develop an improved quality healthcare services using enhanced krill herd optimisation. To increase the KH speed and safeguard against a local optimum, we add the counter-populations during population initialization. We also introduce the impulse operator during the search for the optimal solution to give it the push it needs to quickly escape a local optimum if it ever enters one. The simulation is conducted to test the efficacy of the krill herd optimisation in improving the healthcare quality services in predicting the heart disease problem in humans. The results show improved classification accuracy than the other methods.