Volume: 2 Issue: 1
Year: 2025, Page: 102-108, Doi: https://doi.org/10.70968/ijeaca.v2i1.D1007
Received: Feb. 22, 2025 Accepted: June 10, 2025 Published: July 22, 2025
Abnormal growths in the kidneys known as kidney tumors can be harmful if they are not discovered in time. It's critical to identify them promptly and accurately in order to save lives. In this study, we employ machine learning, a kind of computer software that learns from data, to make it easier for medical professionals to identify kidney cancers. In order to teach the computer to distinguish between kidneys that are healthy and kidneys that have tumors, we gather medical images of kidneys. To determine the most accurate and efficient approach, many machine learning algorithms are explored. Our findings demonstrate that kidney cancers can be accurately detected by machine learning, speeding up the diagnosis process and assisting medical professionals in making better judgments. With an accuracy of 0.95, Most of the cases were correctly predicted by the study. Furthermore, we focused on precisely identifying the Region of Interest (ROI), or the exact location of the tumor in the kidney. The ROI was effectively highlighted by the study model, assisting physicians in rapidly concentrating on the impacted area.
Keywords: Machine Learning Techniques for Kidney Tumor Detection: A Literature Review
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© 2025 Barshikar & Lokhande. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Barshikar SH, Lokhande SS. (2025). Machine Learning Techniques for Kidney Tumor Detection: A Literature Review. International Journal of Electronics and Computer Applications. 2(1): 102-108. https://doi.org/10.70968/ijeaca.v2i1.D1007