University of Bahrain
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Intelligent Identification of Liver Diseases (IILD) based on Incremental Hidden Layer Neurons ANN Model

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dc.contributor.author Terlapu, Panduranga Vital
dc.contributor.author Sadi, Ram Prasad Reddy
dc.contributor.author Pondreti, Ram Kishor
dc.contributor.author Tippana, Chalapathi Rao
dc.date.accessioned 2021-07-27T06:05:53Z
dc.date.available 2021-07-27T06:05:53Z
dc.date.issued 2021-07-27
dc.identifier.issn 2210-142X
dc.identifier.uri https://journal.uob.edu.bh:443/handle/123456789/4352
dc.description.abstract The liver is a crucial and big organ in the human body, impacts the digestion system. Due to Liver diseases (LDs), so many deaths are occurred in worldwide that nearly 2 million deaths per year. The main LD complications are cirrhosis that 11th position in universal deaths, and others hepatocellular carcinoma and viral hepatitis that 16th leading position for global deaths. Fortunately, 3.5% of deaths are occurred due to LD. The capability of an ML approach for controlling LD can be identified through their factors, cofactors as well as complications respectively. In this research, we gather the personal and clinical information about1460 individuals with 17 LD feature attributes include diagnosis class attribute from 2018 to 2020 with good questionnaire from north coastal districts of A.P., India hospitals, and reputed clinical centers. We apply machine learning (ML) models like Logistic Regression (LR), SVM with RBF kernel, Naive Bayes (NB), KNN, and Decision Tree (DT or Tree). As per the ML model’s analysis, the DT model presents the superior classification accuracy that value is 0.9712 (97.12%) than other experimental ML models for the collected LD dataset. Our proposal model incremental hidden layer (HL) neurons ANN (Artificial Neural Network) solutes LD detection with the highest classification and testing accuracy that the value is 0.999 (99.9%) at the 30 HL neurons. en_US
dc.language.iso en en_US
dc.publisher University of Bahrain en_US
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/ *
dc.subject Liver Disease en_US
dc.subject Machine Learning en_US
dc.subject ANN en_US
dc.subject Neural Networks en_US
dc.title Intelligent Identification of Liver Diseases (IILD) based on Incremental Hidden Layer Neurons ANN Model en_US
dc.contributor.authorcountry India en_US
dc.contributor.authorcountry India en_US
dc.contributor.authorcountry India en_US
dc.contributor.authorcountry India en_US
dc.contributor.authoraffiliation Aditya Institute of Technology and Management, Tekkali, Srikakulam, A.P en_US
dc.contributor.authoraffiliation Anil Neerukonda Institute of Technology and Sciences, Visakhapatnam, A.P en_US
dc.contributor.authoraffiliation Aditya Institute of Technology and Management, Tekkali, Srikakulam, A.P en_US
dc.contributor.authoraffiliation Aditya Institute of Technology and Management, Tekkali, Srikakulam, A.P en_US
dc.source.title International Journal of Computing and Digital System en_US
dc.abbreviatedsourcetitle IJCDS en_US


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