STUDY OF CRITICAL DISEASES RISK FACTOR FROM ECG SIGNAL BY MEANS OF ARTIFICIAL INTELLIGENCE

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Abstract

Health study analysis is sometimes supported a comparison of derived health measures to predefined thresholds. Symptoms are often discovered if a worth is on top of or below a threshold. Early detection of signs of heart stroke  permits the prediction of strokes of cardiopathy and may so forestall these. Therefore, the characteristic "accurate" criteria is that the most vital task. The accuracy of associate degree experiment depends powerfully on the accuracy of the standards used. Symptom cardiopathy (CHF) happens once the guts cannot pump enough blood for a stable physiological state. CHF typically happens once the arteria blockage causes the guts tissue to become acidic. {the knowledge /the info/the information} accustomed analyze data like rectilinear regression, Missing Enrollment knowledge, Search Signal, Clinical knowledge Protection Programs, and Early accommodative Alarm. 

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How to Cite
[1]
“STUDY OF CRITICAL DISEASES RISK FACTOR FROM ECG SIGNAL BY MEANS OF ARTIFICIAL INTELLIGENCE”, IEJRD - International Multidisciplinary Journal, vol. 6, no. ICMRD21, p. 8, Apr. 2021.

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