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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM18966
Volume:
7 |
4 |
Apr 2023
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.
Thyroid detection is an important medical diagnosis task that requires accurate and efficient methods. In this paper, we propose using the Random Forest algorithm for detecting the presence of thyroid in a person using machine learning. We trained the algorithm on a dataset of thyroid images and evaluated its performance using various metrics. Our results demonstrate that the Random Forest algorithm is a reliable and accurate method for detecting the presence of thyroid in a person.
KEYWORDS
Publication Date
5/5/2023
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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No funding information available for this research.
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