Human Diseases Detection Based On Machine Learning Algorithms: A Review
Nareen O. M. Salim & Adnan Mohsin Abdulazeez
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.
|Title:||Human Diseases Detection Based On Machine Learning Algorithms: A Review|
|Author:||Nareen O. M. Salim & Adnan Mohsin Abdulazeez|
|Journal Name:||International Journal of Science and Business|
|ISSN:||ISSN 2520-4750 (Online), ISSN 2521-3040 (Print)|
|Date of Publication:||25/01/2021|
|Paper Type:||Literature Review|
Cite This Article:
Nareen O. M. Salim & Adnan Mohsin Abdulazeez (2021). Human Diseases Detection Based On Machine Learning Algorithms: A Review. International Journal of Science and Business, 5(2), 102-113. doi: https://doi.org/10.5281/zenodo.4462858
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About Author (s)
Nareen O. M. Salim, Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq.
Adnan Mohsin Abdulazeez (corresponding author), Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq. Email: email@example.com