Automated Detection of Normal and Cardiac Heart Disease Using Chaos Attributes and Online Sequential Extreme Learning Machine-Reference-Cited by-同舟云学术

Automated Detection of Normal and Cardiac Heart Disease Using Chaos Attributes and Online Sequential Extreme Learning Machine

Published:2021 Issue: Volume: Page:213-234
ISSN:2366-0988
Container-title:Health Information Science
language:
Short-container-title:

Author:

Singh Ram Sewak,Gelmecha Demissie Jobir,Aseffa Dereje Tekilu,Ayane Tadesse Hailu,Sinha Devendra Kumar

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-68723-6_11

Reference65 articles.

1. B. L. Dake and C. L. Oltman, “Cardiovascular, metabolic, and coronary dysfunction in high-Fat-Fed obesity-resistant/prone rats,” Obesity, vol. 23, no. 3, pp. 623–629, 2015, doi: https://doi.org/10.1002/oby.21009.

2. World Health Organization, “Noncommunicable Diseases. Country Perfil 2011,” World Health Organization, 2011. http://www.who.int/nmh/publications/ncd_profiles2011/en/.

3. S. Yusuf et al., “Cardiovascular Risk and Events in 17 Low-, Middle-, and High-Income Countries,” N. Engl. J. Med., vol. 371, no. 9, pp. 818–827, 2014, doi: https://doi.org/10.1056/NEJMoa1311890.

4. D. Prabhakaran et al., “Two-year outcomes in patients admitted with non-ST elevation acute coronary syndrome: results of the OASIS registry 1 and 2.” Indian Heart J., vol. 57, no. 3, pp. 217–25, 2005, [Online]. Available: http://www.ncbi.nlm.nih.gov/pubmed/16196178.

5. A. Bayés De Luna, “Nueva terminología de las paredes del corazón y nueva clasificación electrocardiográfica de los infartos con onda Q basada en la correlación con la resonancia magnética,” Revista Espanola de Cardiologia, vol. 60, no. 7, pp. 683–689, 2007.