Liver Disease Prediction Using Deep Learning

Abstract: Liver, a crucial interior organ of the human body whose principal tasks are to eliminate generated waste produced by our organism, digest food, and preserve vitamins and energy materials. The liver disorder can cause various fatal diseases, including liver cancer. Early diagnosis, and treating the patients are compulsory to reduce the risk of those lethal diseases. we attempted to find a model which can predict the occurrence of liver disease in a given patient with the highest accuracy, based on different input factors. A dataset was chosen to train and test this model; Indian Liver Patient Dataset obtained . We implemented different deep learning algorithms (Multi- Layer Perceptron, Stochastic Gradient Descent, RestrictedBoltzmann) and filtered out the DL-based MLP (Multi-Layer Perceptron) model as the one providing the highest Accuracy, which was compared f or each model along with the Precision, Recall andf1 scores.

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Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2024-11-27
DOI
https://doi.org/10.22214/ijraset.2024.65426
Primary Topic
Artificial Intelligence in Healthcare
Type
article
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article

Liver Disease Prediction Using Deep Learning

T. Bharath Kumar, A. Lavanya, A. Priya, P Sandhya et al.
International Journal for Research in Applied Science and Engineering Technology
Artificial Intelligence in Healthcare
article

Liver Disease Prediction Using Deep Learning

T. Bharath Kumar, A. Lavanya, A. Priya, P Sandhya, V. Jyoshita, B. Harshini
article en

Abstract

Abstract: Liver, a crucial interior organ of the human body whose principal tasks are to eliminate generated waste produced by our organism, digest food, and preserve vitamins and energy materials. The liver disorder can cause various fatal diseases, including liver cancer. Early diagnosis, and treating the patients are compulsory to reduce the risk of those lethal diseases. we attempted to find a model which can predict the occurrence of liver disease in a given patient with the highest accuracy, based on different input factors. A dataset was chosen to train and test this model; Indian Liver Patient Dataset obtained . We implemented different deep learning algorithms (Multi- Layer Perceptron, Stochastic Gradient Descent, RestrictedBoltzmann) and filtered out the DL-based MLP (Multi-Layer Perceptron) model as the one providing the highest Accuracy, which was compared f or each model along with the Precision, Recall andf1 scores.

International Journal for Research in Applied Science and Engineering TechnologyVol. 12(11)
Responsible consumption and production
Openalex Percentile: Top 70%
Artificial Intelligence in Healthcare
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