• Dr. Dinesh D. Patil
• Mr. Manish Sunil Wadile

Electrocardiogram arrhythmias are abnormal heart rhythms that can lead to serious medical conditions if undetected. Early and accurate detection of arrhythmia will play an important role in patient care. In this paper, we proposed a more optimized approach for detecting and analyzing arrhythmia using the MIT database. The classification is done for the Detection of abnormal heart rhythms using a Support vector machine (SVM) and Island-based Cuckoo Search with a highly disruptive polynomial mutation (iCSPM) Optimized Neural network.

Machine Learning; support vector machine; Electrocardiogram; Island-based cuckoo search; iCSPM; Neural Network

"Survey for Analysis of ECG Arrhythmia for Heart Disease Using SVM and Island-based Cuckoo Search with Highly Disruptive Polynomial Mutation ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 10, page no.g742-g744, October-2023, Available :http://www.jetir.org/papers/JETIR2310585.pdf

"Survey for Analysis of ECG Arrhythmia for Heart Disease Using SVM and Island-based Cuckoo Search with Highly Disruptive Polynomial Mutation ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 10, page no. ppg742-g744, October-2023, Available at : http://www.jetir.org/papers/JETIR2310585.pdf