University of Bahrain
Scientific Journals

Taxonomy on Healthcare System Based on Machine Learning

Show simple item record Karmani, Priyanka Chandio, Aftab Ahmed Karmani, Vivekanand Korejo, Imtiaz Ali Chandio, Muhammad Saleem 2020-07-20T11:59:54Z 2020-07-20T11:59:54Z 2020-11-01
dc.identifier.issn 2210-142X
dc.description.abstract This study enlightens the impact of Machine Learning algorithms and practices in the context of Healthcare Informatics. In the domain of Healthcare Informatics (HI), Machine Learning (ML) procedures have been classified into four classes named as ML-HI types, ML-HI approaches, ML-HI paradigms and ML-HI algorithms. In this study, we provide an overview of the state-of-the-art, the research challenges, and the forthcoming directions, specifically driven to the diagnosis of Tuberculosis (TB) disease. Moreover, we introduce our proposed framework for TB diagnosis disease based on ML. We emphasized the strengths and weaknesses of the studied methods facilitate to the aid analysis community to pick the suitable technique to use within the Healthcare Informatics domain. en_US
dc.language.iso en en_US
dc.publisher University of Bahrain en_US
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International *
dc.rights.uri *
dc.subject machine learning; healthcare informatics; tuberculosis; en_US
dc.title Taxonomy on Healthcare System Based on Machine Learning en_US
dc.volume 9 en_US
dc.issue 6
dc.pagestart 1199 en_US
dc.pageend 1212 en_US
dc.source.title International Journal of Computing and Digital Systems en_US
dc.abbreviatedsourcetitle IJCDS en_US

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