• Leena B Chaudhari
• Dr.Dhananjay E. Upasani
• Dr. Anupama Deshpande

Abstract: Health data analysis is usually based on a comparison of derived health measures to predefined thresholds. Symptoms can be observed if a value is above or below a threshold. Early detection of signs of heart failure allows the prediction of strokes of heart failure and can therefore prevent these. So identifying "accurate" criteria is the most important task. The accuracy of an experiment depends strongly on the accuracy of the criteria used. Congestive heart failure (CHF) occurs when the heart cannot pump sufficient blood for a stable physiological condition. CHF usually occurs when the coronary artery blockage causes the heart tissue to become acidic. The data used to analyze data such as Linear Regression, Missing Enrollment Data, Search Signal, Clinical Data Protection Programs, and Early Adaptive Alarm. In this article, the program tracks the heart disease patients, predicts atrial fibrillation and ventricular fibrillation, and alerts patients when the critical condition occurs.

Keywords: Congestive heart failure.

"Analysis of Critical diseases from ECG signal using Artificial Intelligence: A Review.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 11, page no.844-847, November-2020, Available :http://www.jetir.org/papers/JETIR2011251.pdf

"Analysis of Critical diseases from ECG signal using Artificial Intelligence: A Review.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 11, page no. pp844-847, November-2020, Available at : http://www.jetir.org/papers/JETIR2011251.pdf