Novel deep learning-based solution for identification of prognostic subgroups in liver cancer (Hepatocellular carcinoma)

Novel deep learning-based solution for identification of prognostic subgroups in liver cancer (Hepatocellular carcinoma)

Background: Liver cancer (Hepatocellular carcinoma; HCC) prevalence is increasing and with poor clinical outcome expected it means greater understanding of HCC aetiology is urgently required. This study explored a deep learning solution to detect biologically important features that distinguish prog...

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Bibliographic Details
Main Authors: Jurek-Loughrey, A. (Author), McArt, D.G (Author), McInerney, C.E (Author), Owens, A.R (Author), Prise, K.M (Author)
Format: Article
Language:English
Published: BioMed Central Ltd 2021
Subjects:
Alkylation
Auto encoders
Autoencoders
Baseline models
Bioinformatics
Carcinoma, Hepatocellular
Clinical outcome
Clustering
Clusterings
Deep learning
Deep Learning
Diseases
Feature extraction
genetics
Hepatocellular carcinoma
human
Humans
Information filtering
Liver cancer
Liver cancers
liver cell carcinoma
Liver Neoplasms
liver tumor
messenger RNA
Neural networks
Objective functions
prognosis
Prognosis
Prognostic subgroup
Prognostic subgroups
RNA
RNA, Messenger
Survival analysis
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