DLMNN Based Heart Disease Prediction with PD-SS Optimization Algorithm

作     者：S.Raghavendra Vasudev Parvati R.Manjula Ashok Kumar Nanda Ruby Singh D.Lakshmi S.Velmurugan 

作者机构：Department of Information and Communication TechnologyManipal Institute of TechnologyManipal Academy of Higher EducationManipal576104India Department of Information Science and EngineeringSDM College of Engineering and TechnologyDharwad580002India Department of Computer Science and EngineeringSchool of ComputingSRM Institute of Science and TechnologyKattankulathurChennai603203India Department of Computer Science and EngineeringB.V Raju Institute of TechnologyTelangana502313India Faculty of Engineering and TechnologySRM Institute of Science and TechnologyNCR CampusUttar Prasesh201204India School of Computing Science and EngineeringVIT Bhopal UniversityMadhya Pradesh466114India Department of Computer Science and EngineeringVel Tech Multi Tech Dr.Rangarajan Dr.Sakunthala Engineering CollegeChennai600062India 

出 版 物：《Intelligent Automation & Soft Computing》 (智能自动化与软计算（英文）)

年 卷 期：2023年第35卷第2期

页      面：1353-1368页

核心收录：

学科分类：1002[医学-临床医学] 100201[医学-内科学(含：心血管病、血液病、呼吸系病、消化系病、内分泌与代谢病、肾病、风湿病、传染病)] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 10[医学] 

主　　题：Machine learning random forest coronary heart disease cardiovascular optimization algorithm 

摘      要：In contemporary medicine,cardiovascular disease is a major public health *** diseases are one of the leading causes of death *** are classified as vascular,ischemic,or *** information contained in patients’Electronic Health Records(EHR)enables clin-icians to identify and monitor heart *** failure rates have risen drama-tically in recent years as a result of changes in modern *** diseases are becoming more prevalent in today’s medical *** year,a substantial number of people die as a result of cardiac *** primary cause of these deaths is the improper use of pharmaceuticals without the supervision of a physician and the late detection of *** improve the efficiency of the classification algo-rithms,we construct a data pre-processing stage using feature ***-ments using unidirectional and bidirectional neural network models found that a Deep Learning Modified Neural Network(DLMNN)model combined with the Pet Dog-Smell Sensing(PD-SS)algorithm predicted the highest classification performance on the UCI Machine Learning Heart Disease *** DLMNN-based PDSS achieved an accuracy of 94.21%,an F-score of 92.38%,a recall of 94.62%,and a precision of 93.86%.These results are competitive and promising for a heart disease *** demonstrated that a DLMNN framework based on deep models may be used to solve the categorization problem for an unbalanced heart disease *** proposed approach can result in exceptionally accurate models that can be utilized to analyze and diagnose clinical real-world data.