ISSN 2394-5125
 

Review Article 


REVIEW OF CONTEMPORARY LITERATURE ON PREDICTIVE ANALYSIS FOR ARRHYTHMIA DISEASE DETECTION

S.Aarathi, Dr.S.Vasundra.

Abstract
In the area of data engineering,machine learning, as well as data mining are some of the primary measures, which
can be adopted for the optimization of computer-guided data retrieval and also for the recovery of information. In
most of the studies, which are currently being carried out in the area of computer-guided diagnosis are mainly linked
to machine learning, as well as to data extraction approaches. Different kinds of information, which have linked to
the patients in different designs like EER, EMR, and medical imaging points out some of the significant benefits,
which are associated with data recovery as well as information recovery. However, it is worth pointing out that the
present studies demonstrate that there is a general lack of adequate contributions when it comes to retrieving
information as well as data. As a result, this work provides a systematic review, which points out some of the main
concerns, problems as well as benchmarking predictive analysis tools that are in existence, and which have explored
by the modern literature.

Key words: ECG (Electro Cardio Gram), Machine learning (ML), Coronary artery disease (CAD), MATLAB tool, SVM classifier, Bacterial foraging optimization algorithm (BFOA).


 
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Pubmed Style

S.Aarathi, Dr.S.Vasundra. REVIEW OF CONTEMPORARY LITERATURE ON PREDICTIVE ANALYSIS FOR ARRHYTHMIA DISEASE DETECTION. JCR. 2020; 7(18): 394-401. doi:10.31838/jcr.07.18.58


Web Style

S.Aarathi, Dr.S.Vasundra. REVIEW OF CONTEMPORARY LITERATURE ON PREDICTIVE ANALYSIS FOR ARRHYTHMIA DISEASE DETECTION. http://www.jcreview.com/?mno=31052 [Access: July 07, 2020]. doi:10.31838/jcr.07.18.58


AMA (American Medical Association) Style

S.Aarathi, Dr.S.Vasundra. REVIEW OF CONTEMPORARY LITERATURE ON PREDICTIVE ANALYSIS FOR ARRHYTHMIA DISEASE DETECTION. JCR. 2020; 7(18): 394-401. doi:10.31838/jcr.07.18.58



Vancouver/ICMJE Style

S.Aarathi, Dr.S.Vasundra. REVIEW OF CONTEMPORARY LITERATURE ON PREDICTIVE ANALYSIS FOR ARRHYTHMIA DISEASE DETECTION. JCR. (2020), [cited July 07, 2020]; 7(18): 394-401. doi:10.31838/jcr.07.18.58



Harvard Style

S.Aarathi, Dr.S.Vasundra (2020) REVIEW OF CONTEMPORARY LITERATURE ON PREDICTIVE ANALYSIS FOR ARRHYTHMIA DISEASE DETECTION. JCR, 7 (18), 394-401. doi:10.31838/jcr.07.18.58



Turabian Style

S.Aarathi, Dr.S.Vasundra. 2020. REVIEW OF CONTEMPORARY LITERATURE ON PREDICTIVE ANALYSIS FOR ARRHYTHMIA DISEASE DETECTION. Journal of Critical Reviews, 7 (18), 394-401. doi:10.31838/jcr.07.18.58



Chicago Style

S.Aarathi, Dr.S.Vasundra. "REVIEW OF CONTEMPORARY LITERATURE ON PREDICTIVE ANALYSIS FOR ARRHYTHMIA DISEASE DETECTION." Journal of Critical Reviews 7 (2020), 394-401. doi:10.31838/jcr.07.18.58



MLA (The Modern Language Association) Style

S.Aarathi, Dr.S.Vasundra. "REVIEW OF CONTEMPORARY LITERATURE ON PREDICTIVE ANALYSIS FOR ARRHYTHMIA DISEASE DETECTION." Journal of Critical Reviews 7.18 (2020), 394-401. Print. doi:10.31838/jcr.07.18.58



APA (American Psychological Association) Style

S.Aarathi, Dr.S.Vasundra (2020) REVIEW OF CONTEMPORARY LITERATURE ON PREDICTIVE ANALYSIS FOR ARRHYTHMIA DISEASE DETECTION. Journal of Critical Reviews, 7 (18), 394-401. doi:10.31838/jcr.07.18.58





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