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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM34605
Volume:
8 |
5 |
May 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
â Among the most crucial concerns facing society is healthcare for humans. It looks for the most accurate diagnostic and comprehensive illness in order to guarantee that patients get the care they need as soon as feasible. Because this recognition is often difficult, additional fields are needed for the health-related component of searching, such as computer science and statistics[3]. To adopt novel approaches, these disciplines need to go beyond the conventional ones. Since there are so many novel approaches, it is feasible to provide an overview without going into specifics. To this end, we suggest a comprehensive analysis of illnesses associated with machine learning in humans. This research focuses on current methods related to machine learning growth applied to the diagnosis of human illnesses in the medical business in order to identify intriguing trends, generate insignificant forecasts, and support decision-making[1]. This study explores unique machine learning techniques used in healthcare applications to generate appropriate decision support[4], [5]. This work aims to close the research gap by creating a workable decision support system for medical applications.
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Publication Date
5/27/2024
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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