Paper Title
LIVER DISEASE PREDICTION USING MACHINE LEARNING
Article Identifiers
Authors
R JEGADEESAN , K.MEGHANA , E.PRAVEEN , N.VIVEK , G.SRIKANTH
Keywords
LIVER DISEASE PREDICTION USING MACHINE LEARNING
Abstract
In Human beings, Liver is the most primary a part of the frame that plays many features along with the production of Bile, excretion of bile and bilirubin, metabolism of proteins and carbohydrates, activation of Enzymes, Storing glycogen, vitamins, and minerals, plasma proteins synthesis and clotting factors. The liver effortlessly receives affected because of intake of alcohol, ache killer capsules, food conduct, and includes lots of stressed out practices. Currently, the liver associated illnesses are recognized by analyzing liver characteristic blood check reports and test reports. It takes greater time as well as luxurious. While employing unique statistics mining algorithms to ease this process it's miles feasible to reduce the time for diagnosing the liver ailment. When greater information are used, the prediction may be greater correct. To avoid the neighborhood garage scarcity experienced in many healthcare centers, cloud garage is used. As the files generated are voluminous in size in fitness care facilities cloud storage might be the perfect preference.
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How To Cite (APA)
R JEGADEESAN, K.MEGHANA, E.PRAVEEN, N.VIVEK, & G.SRIKANTH (May-2024). LIVER DISEASE PREDICTION USING MACHINE LEARNING. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(5), g603-g607. https://ijnrd.org/papers/IJNRD2405669.pdf
Issue
Volume 9 Issue 5, May-2024
Pages : g603-g607
Other Publication Details
Paper Reg. ID: IJNRD_222269
Published Paper Id: IJNRD2405669
Downloads: 000121985
Research Area: Engineering
Country: -, -, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2405669.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2405669
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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition
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