An exhaustive review of machine and deep learning based diagnosis of heart diseases

被引:0
作者
Adyasha Rath
Debahuti Mishra
Ganapati Panda
Suresh Chandra Satapathy
机构
[1] Siksha O Anusandhan (Deemed To Be) University,Department of Computer Science and Engineering
[2] C. V. Raman Global University,Department of Electronics and Tele Communication
[3] KIIT Deemed To Be University,School of Computer Engineering
来源
Multimedia Tools and Applications | 2022年 / 81卷
关键词
CVD; Detection of HD using ML; Diagnosis of HD; Review and analysis of HD; IoT based HD; CNN in HD detection;
D O I
暂无
中图分类号
学科分类号
摘要
In comparison to other diseases, the number of deaths on Heart Disease (HD) is the highest across the globe. The trend of death due to HD is still rising which has become a constant source of concern amongst the human beings. The researchers and doctors are putting tremendous efforts to save the life from HD. It is observed from the literature that a large number of researchers are currently carrying out their research work in various aspects of HD. Among those the early detection and diagnosis of HD are currently the focus area of research. Appropriate, reliable, accurate, robust and affordable HD detection scheme is the ultimate goal for saving the lives of the people. In this research, articles on HD detection and diagnosis published in recent past have been collected and critically analysed. The outcome of the analysis is presented in various tabular forms for easy understanding and further use. The paper would provide a thorough knowledge on standard data source on HD, the feature extraction, selection and reduction methods and Machine Learning (ML) and Deep Learning (DL) based classification schemes. The categorization of published articles and the various performance measures employed have been presented which would develop interest amongst new researchers working in the area of detection or classification of HD. The best performing technique in each category of has been listed. The research challenges and future scope of work are also provided to facilitate further research work in this promising area.
引用
收藏
页码:36069 / 36127
页数:58
相关论文
共 162 条
  • [11] Turkoglu I(2009)Effective diagnosis of heart disease through neural networks ensembles Expert Syst Appl 36 7675-83
  • [12] Babaoglu İ(2018)Extracting cardiac dynamics within ECG signal for human identification and cardiovascular diseases classification Neural Netw 100 70-34
  • [13] Findik O(2017)Deep neural networks for the recognition and classification of heart murmurs using neuromorphic auditory sensors IEEE Trans Biomed Circuits Syst 12 24-693
  • [14] Ülker E(2018)Performance evaluation of different machine learning techniques for prediction of heart disease Neural Comput Appl 29 685-59256
  • [15] Bashir S(2020)Recursion enhanced random forest with an improved linear model (RERF-ILM) for heart disease detection on the internet of medical things platform IEEE Access 8 59247-4238
  • [16] Qamar U(2009)An expert system based on least square support vector machines for diagnosis of the valvular heart disease Expert Syst Appl 36 4232-140
  • [17] Khan FH(2019)Deep learning approach to cardiovascular disease classification employing modified ECG signal from empirical mode decomposition Biomed Signal Process Control 52 128-180243
  • [18] Javed MY(2019)An intelligent learning system based on random search algorithm and optimized random forest model for improved heart disease detection IEEE Access 7 180235-89
  • [19] Başçiftçi F(2008)Design of a hybrid system for the diabetes and heart diseases Expert Syst Appl 35 82-8542
  • [20] İncekara H(2010)A fuzzy-evidential hybrid inference engine for coronary heart disease risk assessment Expert Syst Appl 37 8536-34727