Liver cancer prediction in a viral hepatitis cohort: A deep learning approach.
Adolescent
Adult
Age Factors
Child
Child, Preschool
Deep Learning
Female
Hepatitis, Viral, Human
/ epidemiology
Humans
Infant
Infant, Newborn
Liver Neoplasms
/ epidemiology
Longitudinal Studies
Male
Middle Aged
Neural Networks, Computer
Prevalence
Registries
Retrospective Studies
Taiwan
/ epidemiology
Young Adult
deep learning
hepatitis
liver cancer
Journal
International journal of cancer
ISSN: 1097-0215
Titre abrégé: Int J Cancer
Pays: United States
ID NLM: 0042124
Informations de publication
Date de publication:
15 11 2020
15 11 2020
Historique:
received:
20
05
2020
revised:
15
07
2020
accepted:
28
07
2020
pubmed:
8
8
2020
medline:
17
4
2021
entrez:
8
8
2020
Statut:
ppublish
Résumé
Viral hepatitis is the primary cause of liver diseases, among which liver cancer is the leading cause of death from cancer. However, this cancer is often diagnosed in the later stages, which makes treatment difficult or even impossible. This study applied deep learning (DL) models for the early prediction of liver cancer in a hepatitis cohort. In this study, we surveyed 1 million random samples from the National Health Insurance Research Database (NHIRD) to analyze viral hepatitis patients from 2002 to 2010. Then, we used DL models to predict liver cancer cases based on the history of diseases of the hepatitis cohort. Our results revealed the annual prevalence of hepatitis in Taiwan increased from 2002 to 2010, with an average annual percentage change (AAPC) of 5.8% (95% CI: 4.2-7.4). However, young people (aged 16-30 years) exhibited a decreasing trend, with an AAPC of -5.6 (95% CI: -8.1 to -2.9). The results of applying DL models showed that the convolution neural network (CNN) model yielded the best performance in terms of predicting liver cancer cases, with an accuracy of 0.980 (AUC: 0.886). In conclusion, this study showed an increasing trend in the annual prevalence of hepatitis, but a decreasing trend in young people from 2002 to 2010 in Taiwan. The CNN model may be applied to predict liver cancer in a hepatitis cohort with high accuracy.
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
2871-2878Informations de copyright
© 2020 UICC.
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