Human Diseases Detection Based On Machine Learning Algorithms: A Review
Nareen O. M. Salim and
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Nareen O. M. Salim: Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq
International Journal of Science and Business, 2021, vol. 5, issue 2, 102-113
One of the most significant subjects of society is human healthcare. It is looking for the best one and robust disease diagnosis to get the care they need as soon as possible. Other fields, such as statistics and computer science, are needed for the health aspect of searching since this recognition is often complicated. The task of following new approaches is challenging these disciplines, moving beyond the conventional ones. The actual number of new techniques makes it possible to provide a broad overview that avoids particular aspects. To this end, we suggest a systematic analysis of human diseases related to machine learning. This research concentrates on existing techniques related to machine learning growth applied to the diagnosis of human illnesses in the medical field to discover exciting trends, make unimportant predictions, and help decision-making. This paper analyzes unique machine learning algorithms used for healthcare applications to create adequate decision support. This paper intends to reduce the research gap in creating a realistic decision support system for medical applications.
Keywords: Human disease; Healthcare; Machine learning; Deep learning; Convolutional Neural Networks (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:aif:journl:v:5:y:2021:i:2:p:102-113
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