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Cite Article
MLA
Saxena, Arti, and Vijay Kumar. "Bayesian Kernel Methods: Applications in Medical Diagnosis Decision-Making Processes (A Case Study)." IJBDAH vol.6, no.1 2021: pp.26-39. http://doi.org/10.4018/IJBDAH.20210101.oa3
APA
Saxena, A. & Kumar, V. (2021). Bayesian Kernel Methods: Applications in Medical Diagnosis Decision-Making Processes (A Case Study). International Journal of Big Data and Analytics in Healthcare (IJBDAH), 6 (1), 26-39. http://doi.org/10.4018/IJBDAH.20210101.oa3
Chicago
Saxena, Arti, and Vijay Kumar. "Bayesian Kernel Methods: Applications in Medical Diagnosis Decision-Making Processes (A Case Study)," International Journal of Big Data and Analytics in Healthcare (IJBDAH) 6, no.1: 26-39. http://doi.org/10.4018/IJBDAH.20210101.oa3
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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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