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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM38922
Volume:
8 |
11 |
Nov 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.
Liver disease is a widespread medical condition that impacts a substantial proportion of the world’s population. Liver disease can be caused by a number of things, including drinking too much alcohol, being around contaminated or damaged food, using drugs, being exposed to pollutants released by chemical plants, and being obese. Given the liver’s crucial function in detoxifying, a diagnosis and recovery from liver disease depend heavily on early identification. The approach that this research suggests uses Convolutional Neural Networks (CNNs) to improve the efficacy and precision of liver disease detection. By facilitating early diagnosis, the suggested system hopes to enhance patient outcomes and enable prompt medical interventions.
KEYWORDS
Publication Date
11/18/2024
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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