Machine Learning (ML) and Artificial Intelligence (AI) methods are transforming many commercial and academic areas, including feature extraction, autonomous driving, computational linguistics, and voice recognition. These new technologies are now having a significant effect in radiography, forensics, and many other areas where the accessibility of automated systems may improve the precision and repeatability of essential job performance. In this systematic review, we begin by providing a short overview of the different methods that are currently being developed, with a particular emphasis on those utilized in biomedical studies.
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Cite this article
Yung Ming and Lily Yuan, “Supervised Learning Methods and Applications in Medical Research”, Journal of Computing and Natural Science, vol.2, no.1, pp. 027-034, January 2022. doi: 10.53759/181X/JCNS202202005.
