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AUTHOR(S): P. Tamije Selvy, B.goutham Sabaries
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TITLE Diagnosing Liver Disorder by Using Machine Learning Techniques |
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ABSTRACT The liver is an important part in the body producing proteins and blood condensing to soaked fat, sugar, and all other digestion activities. Liver has many purposes, counting and removing toxics from the body, and is essential to happen. It has an extensive diversity of purposes which comprises earlier estimate of any sickness is very noteworthy to support human natural life and yield appropriate stages to eradicate the sickness. AI approaches actively busy in foremost categories of therapeutic information. This proposed project work has initial enquiry and forecast of liver disorder by means of various machine learning and deep learning methods and the project model is examined by various performance measures such as recall, precision and accuracy. A tabular analysis is carried out by using some methods such as naive bayes and logistic regression. We have optimised the project model by using ensemble methods such as XG boost and random forest classifiers. At last, we have applied neural networks for getting maximum accuracy |
KEYWORDS Liver disorder, Therapeutic information, AI, Prediction, Comparison |
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Cite this paper P. Tamije Selvy, B.goutham Sabaries. (2021) Diagnosing Liver Disorder by Using Machine Learning Techniques. International Journal of Economics and Management Systems, 6, 336-339 |
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