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International Journal of Research and Scientific Innovation (IJRSI)

An Evaluation of Deep Learning in the processing of Medical Images

byAnchal Kumari; Vikas Kumar; Ankita Kumari

Published September 22, 2025  •  Vol. 12, Issue 8, pp. 2354–2365Open Access
DOI: 10.51244/IJRSI.2025.120800212

Abstract

AI is getting better all the time, especially when it comes to deep learning techniques. This is helping to find, sort, and count patterns in clinical photos. Deep learning is the fastest-growing area of artificial intelligence, and it has been used successfully in many fields, including medicine. There is a short overview of research done in the areas of neuro, brain, retinal, pneumonic, computerized pathology, bosom, heart, breast, bone, stomach, and musculoskeletal. Deep learning networks can be used on massive data to find information, use knowledge, and make predictions based on knowledge. This paper talks about basic information and cutting-edge technologies for medical image processing and analysis that use deep learning. The main goals of this study are to show research on processing medical images and to identify and put into action the main guidelines that are found and talked about.

Keywords: Evaluation ,Deep Learning ,processing ,Medical Images

JournalInternational Journal of Research and Scientific Innovation (IJRSI)
ISSN2321-2705
Volume / IssueVolume 12, Issue 8
Pages2354–2365
Publication dateSeptember 22, 2025
DOI10.51244/IJRSI.2025.120800212
PublisherRSIS International
LicenseOpen Access

How to cite this article

Anchal Kumari, Vikas Kumar, & Ankita Kumari (2025). An Evaluation of Deep Learning in the processing of Medical Images. International Journal of Research and Scientific Innovation (IJRSI), 12(8), 2354-2365. https://doi.org/10.51244/IJRSI.2025.120800212

BibTeX

@article{Anchal2025,
  title   = {An Evaluation of Deep Learning in the processing of Medical Images},
  author  = {Anchal Kumari and Vikas Kumar and Ankita Kumari},
  journal = {International Journal of Research and Scientific Innovation (IJRSI)},
  volume  = {12},
  number  = {8},
  pages   = {2354--2365},
  year    = {2025},
  doi     = {10.51244/IJRSI.2025.120800212},
  publisher = {RSIS International}
}