Optimization of Deep Neural Networks with Particle Swarm Optimization Algorithm for Liver Disease Classification

Samsuryadi, Samsuryadi and Dian Palupi, Rini (2023) Optimization of Deep Neural Networks with Particle Swarm Optimization Algorithm for Liver Disease Classification. Computer Engineering and Applications, 12 (1). pp. 49-57. ISSN 2252-5459

Text (Artikel) ARTIKEL - Optimization of Deep Neural Networks.pdf Download (375kB)

Abstract

Liver disease has affected more than one million new patients in the world. which is where the liver organ has an important role function for the body's metabolism in channeling several vital functions. Liver disease has symptoms including jaundice, abdominal pain, fatigue, nausea, vomiting, back pain, abdominal swelling, weight loss, enlarged spleen and gallbladder and has abnormalities that are very difficult to detect because the liver works as usual even though some liver functions have been damaged. Diagnosis of liver disease through Deep Neural Network classification, optimizing the weight value of neural networks with the Particle Swarm Optimization algorithm. The results of optimizing the PSO weight value get the best accuracy of 92.97% of the Hepatitis dataset, 79.21%, Hepatitis 91.89%, and Hepatocellular 92.97% which is greater than just using a Deep Neural Network.

Item Type:	Article
Subjects:	Q Science > Q Science (General) > Q1-295 General
Divisions:	09-Faculty of Computer Science > 55101-Informatics (S2)
Depositing User:	Dr. Samsuryadi Sahmin
Date Deposited:	18 Apr 2023 03:15
Last Modified:	18 Apr 2023 03:15
URI:	http://repository.unsri.ac.id/id/eprint/96968

Actions (login required)

View Item