Analysis of Heart Disease Using Parallel and Sequential Ensemble Methods With Feature Selection Techniques: Heart Disease Prediction Journal Article

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MLA

Yadav, Dhyan Chandra, and Saurabh Pal. "Analysis of Heart Disease Using Parallel and Sequential Ensemble Methods With Feature Selection Techniques: Heart Disease Prediction." IJBDAH vol.6, no.1 2021: pp.40-56. http://doi.org/10.4018/IJBDAH.20210101.oa4

APA

Yadav, D. C. & Pal, S. (2021). Analysis of Heart Disease Using Parallel and Sequential Ensemble Methods With Feature Selection Techniques: Heart Disease Prediction. International Journal of Big Data and Analytics in Healthcare (IJBDAH), 6(1), 40-56. http://doi.org/10.4018/IJBDAH.20210101.oa4

Chicago

Yadav, Dhyan Chandra, and Saurabh Pal. "Analysis of Heart Disease Using Parallel and Sequential Ensemble Methods With Feature Selection Techniques: Heart Disease Prediction," International Journal of Big Data and Analytics in Healthcare (IJBDAH) 6, no.1: 40-56. http://doi.org/10.4018/IJBDAH.20210101.oa4

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Analysis of Heart Disease Using Parallel and Sequential Ensemble Methods With Feature Selection Techniques: Heart Disease Prediction

International Journal of Big Data and Analytics in Healthcare (IJBDAH)

The International Journal of Big Data and Analytics in Healthcare (IJBDAH) publishes high-quality, scholarly research papers, position papers, and case studies covering: hardware platforms and architectures, development of software methods, techniques and tools, applications and governance and adoption strategies for the use of big data in healthcare and clinical research.The journal has a special focus on new research challenges for informatics arising from the development of longitudinal environmental risk data processing methods (the individual exposome or partial expotypes), including those obtained from personal sensors and devices, clinical records and population/geospatial data. Focusing on key issues, practical applications, and theoretical perspectives, this journal presents research essential to the needs of big data professionals, IT specialists, computer scientists, healthcare analysts, clinical practitioners, and administrators.
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