Investigation of the effectiveness of a classification method based on improved DAE feature extraction for hepatitis C prediction

Hepatitis C, a particularly dangerous form of viral hepatitis caused by hepatitis C virus (HCV) infection, is a major socio-economic and public health problem. Due to the rapid development of deep learning, it has become a common practice to apply deep learning to the healthcare industry to improve...

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Bibliographic Details
Published in:	Scientific reports Vol. 14; no. 1; pp. 9143 - 12
Main Authors:	Zhang, Lin, Wang, Jixin, Chang, Rui, Wang, Weigang
Format:	Journal Article
Language:	English
Published:	London Nature Publishing Group UK 21.04.2024 Nature Publishing Group Nature Portfolio
Subjects:	639/705 692/699/1541 Accuracy Algorithms Autoencoder Classification Deep learning Denoising autoencoder Disease Disease detection Hepacivirus Hepatitis Hepatitis C Hepatitis C - diagnosis Humanities and Social Sciences Humans Machine Learning multidisciplinary Neural networks Neural Networks, Computer Predictions Public health Science Science (multidisciplinary) Warning systems Hepatitis C Autoencoder Denoising autoencoder
ISSN:	2045-2322, 2045-2322
Online Access:	Get full text
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