A proactive intelligent model for identification of reduced factors affecting severity of coronary artery disease and its prediction

Aakash Bhattacharya, Riju Khatri, Tribikram Pradhan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Obesity is an increasingly prevalent metabolic disorder, which results in increased risk of various diseases. One such disease is the coronary artery disease, which is the most common type of heart disease. Coronary artery disease (CAD) leads to the blockage of the arteries, that supply blood to the heart muscles, due to the accumulation of cholesterol and other material called plaque on the inner walls. This makes the arteries narrower and rigid thus restricting blood flow to the heart. In this paper, a model has been proposed to evaluate the severity of CAD among the different classes of obesity based on the prognostic markers and the various causative factors of CAD.

Original languageEnglish
Title of host publication2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1519-1524
Number of pages6
Volume2017-January
ISBN (Electronic)9781509063673
DOIs
Publication statusPublished - 30-11-2017
Event2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017 - Manipal, Mangalore, India
Duration: 13-09-201716-09-2017

Conference

Conference2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017
CountryIndia
CityManipal, Mangalore
Period13-09-1716-09-17

Fingerprint

Identification (control systems)
Blood
Cholesterol
Muscle

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems

Cite this

Bhattacharya, A., Khatri, R., & Pradhan, T. (2017). A proactive intelligent model for identification of reduced factors affecting severity of coronary artery disease and its prediction. In 2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017 (Vol. 2017-January, pp. 1519-1524). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICACCI.2017.8126056
Bhattacharya, Aakash ; Khatri, Riju ; Pradhan, Tribikram. / A proactive intelligent model for identification of reduced factors affecting severity of coronary artery disease and its prediction. 2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017. Vol. 2017-January Institute of Electrical and Electronics Engineers Inc., 2017. pp. 1519-1524
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abstract = "Obesity is an increasingly prevalent metabolic disorder, which results in increased risk of various diseases. One such disease is the coronary artery disease, which is the most common type of heart disease. Coronary artery disease (CAD) leads to the blockage of the arteries, that supply blood to the heart muscles, due to the accumulation of cholesterol and other material called plaque on the inner walls. This makes the arteries narrower and rigid thus restricting blood flow to the heart. In this paper, a model has been proposed to evaluate the severity of CAD among the different classes of obesity based on the prognostic markers and the various causative factors of CAD.",
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Bhattacharya, A, Khatri, R & Pradhan, T 2017, A proactive intelligent model for identification of reduced factors affecting severity of coronary artery disease and its prediction. in 2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017. vol. 2017-January, Institute of Electrical and Electronics Engineers Inc., pp. 1519-1524, 2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017, Manipal, Mangalore, India, 13-09-17. https://doi.org/10.1109/ICACCI.2017.8126056

A proactive intelligent model for identification of reduced factors affecting severity of coronary artery disease and its prediction. / Bhattacharya, Aakash; Khatri, Riju; Pradhan, Tribikram.

2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017. Vol. 2017-January Institute of Electrical and Electronics Engineers Inc., 2017. p. 1519-1524.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - Obesity is an increasingly prevalent metabolic disorder, which results in increased risk of various diseases. One such disease is the coronary artery disease, which is the most common type of heart disease. Coronary artery disease (CAD) leads to the blockage of the arteries, that supply blood to the heart muscles, due to the accumulation of cholesterol and other material called plaque on the inner walls. This makes the arteries narrower and rigid thus restricting blood flow to the heart. In this paper, a model has been proposed to evaluate the severity of CAD among the different classes of obesity based on the prognostic markers and the various causative factors of CAD.

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Bhattacharya A, Khatri R, Pradhan T. A proactive intelligent model for identification of reduced factors affecting severity of coronary artery disease and its prediction. In 2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017. Vol. 2017-January. Institute of Electrical and Electronics Engineers Inc. 2017. p. 1519-1524 https://doi.org/10.1109/ICACCI.2017.8126056