International Journal of Computing and Artificial Intelligence

P-ISSN: 2707-6571, E-ISSN: 2707-658X
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2020, Vol. 1, Issue 1, Part A

Medical image analysis using random forest


Author(s): Shaik Nasarchand

Abstract: The huge achievement of AI calculations at picture acknowledgment assignments lately meets with a period of drastically expanded utilization of electronic therapeutic records and analytic imaging. This audit presents the AI calculations as applied to restorative picture examination, concentrating on convolutional neural systems, and stressing clinical parts of the field. The upside of AI in a time of therapeutic enormous information is that significant hierarchal connections inside the information can be found algorithmically without difficult hand-making of highlights. We spread key research regions and utilizations of therapeutic picture classification, restriction, location, division, and enlistment. We finish up by examining research deterrents, developing patterns, and conceivable future bearings.

DOI: 10.33545/27076571.2020.v1.i1a.6

Pages: 28-31 | Views: 591 | Downloads: 176

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International Journal of Computing and Artificial Intelligence
How to cite this article:
Shaik Nasarchand. Medical image analysis using random forest. Int J Comput Artif Intell 2020;1(1):28-31. DOI: 10.33545/27076571.2020.v1.i1a.6
International Journal of Computing and Artificial Intelligence

International Journal of Computing and Artificial Intelligence

International Journal of Computing and Artificial Intelligence
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