Heart disease detection through early-stage syndrome remains as a main confront in present world situation. If it is not detected appropriate time, then this turns out to be the major cause of death. Several existing heart disease detection techniques are developed with lower detection performance and therefore it is very significant to introduce a novel heart disease detection model that poses the potential to detect heart disease from input data. A novel detection approach named, social water cycle algorithm-based deep residual network (SWCA-based DRN) is proposed for classification of heart disease. The developed SWCA algorithm is a newly designed by the hybridization of social optimization algorithm and water cycle algorithm. Here, an input data is initially preprocessed and the feature fusion procedure is carried out RV coefficient enabled rider optimization algorithm-based neural network. With the fused feature result, heart disease classification is performed utilizing a DRN classifier where training procedure of DRN is done by proposed optimization algorithm, named SWCA. Furthermore, developed SWCA-enabled DRN technique outperformed different other present heart disease detection approaches and attained superior performance concerning the performance measures, like testing accuracy, sensitivity, and specificity with highest values of 0.941, 0.954, and 0.925. K E Y W O R D S deep residual network, heart disease, rider optimization algorithm, social optimization algorithm, water cycle algorithm
INTRODUCTIONA heart is a fundamental organ which expels blood, with life-giving oxygen and supplements to various body tissues. If pumping action of heart becomes ineffective, essential organs such as kidneys as well as brain suffering, and if the heart functioning ceases completely, demise happens in a minute. Heart ailment has been regarded as one of fatal ailments across the world. Life is entirely reliant itself on an effective functioning of heart.The various indications of heart disease encompass weakness of the physical body, fatigue, swollen feet, and shortness of breath. 1,2 In addition, one of the most human life-threatening diseases around a world is heart ailments, due to variations in lifestyle and lack of physical exercise, and obesity is more general among human lives. According to World Health Organization (WHO) data, human deaths are almost 31% of overall and out of which 85% is due to stroke and heart failure. About 17 million people are losing their life due to heart disease every year. 3 Moreover, heart disease is caused based on the threat factors in lifestyle behavior, like sex, age, cholesterol, family history, obesity or inhaling cigarette smoke, improper diet, blood sugar levels, alcohol, high blood pressure, eating foods that are high in fat, and body weight. Certain threat factors are submissive. Furthermore, heart ailment can be partitioned in seven different kinds, namely, arrhythmia, cardiomyopathy, angina pectoris, coronary heart infection, congenital
