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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM36516
Volume:
8 |
7 |
Jul 2024
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.
Kidney disease is a significant global health issue that requires timely and accurate diagnosis to improve patient outcomes. This project presents a deep learning-based kidney classification system designed to assist in the early detection and classification of various kidney conditions using medical imaging data. The proposed system leverages advanced convolutional neural networks (CNNs) to analyze and classify kidney ultrasound and MRI images, distinguishing between healthy kidneys and those affected by diseases such as kidney stones, cysts, and tumors. This methodology enhances the model’s ability to learn intricate patterns and features associated with different kidney conditions, ensuring high classification accuracy and robustness.
KEYWORDS
Publication Date
7/15/2024
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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