COVID-19 Outbreak Based Coronary Heart Diseases (CHD) Prediction Using SVM and Risk Factor Validation
3rd IEEE International Virtual Conference on Innovations in Power and Advanced Computing Technologies, i-PACT 2021
; 2021.
Article
in English
| Scopus | ID: covidwho-1759041
ABSTRACT
Heart disease is a major concern for the medical fraternity under the influence of global pandemic outbreak. According to WHO 17.9 million deaths are reported due to suffering from cardio disease related medical influences and has increased due to comorbidities in outbreak of SARS-CoVID-19 globally. In this research, a focus is on proposing a technique to deal with a predict cognitive approach of classifying and validating the heat diseases risks. The technique is aided with SVM based classifier for decision support via risk factor validation. The technique has provided an improved predictive accuracy and reliability over the risk factor validation caused due to pandemic parameters. © 2021 IEEE.
Coronary Heart Diseases (CHD); Covid-19; Data Mining; Risk factor; Support Vector Machine (SVM); Cardiology; Decision support systems; Diseases; Heart; SARS; Cognitive approaches; Comorbidities; Coronary heart disease; Heart disease; Machine factors; Risk factors; Support vector machine; Support vectors machine; Support vector machines
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Prognostic study
Language:
English
Journal:
3rd IEEE International Virtual Conference on Innovations in Power and Advanced Computing Technologies, i-PACT 2021
Year:
2021
Document Type:
Article
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