Machine learning-based prediction of survival prognosis in cervical cancer

Machine learning-based prediction of survival prognosis in cervical cancer

Background: Accurately forecasting the prognosis could improve cervical cancer management, however, the currently used clinical features are difficult to provide enough information. The aim of this study is to improve forecasting capability by developing a miRNAs-based machine learning survival pred...

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Bibliographic Details
Main Authors: Chen, J. (Author), Ding, D. (Author), Lang, T. (Author), Li, R. (Author), Li, Y. (Author), Liu, J. (Author), Ma, C. (Author), Tan, J. (Author), Wang, D. (Author), Zhou, L. (Author), Zhou, Q. (Author), Zou, D. (Author)
Format: Article
Language:English
Published: BioMed Central Ltd 2021
Subjects:
algorithm
Algorithms
Cancer stem cells
Cervical cancer
Diagnosis
Diseases
female
Female
Forecasting
Forecasting capability
genetics
human
Humans
K-means clustering
Log transformation
machine learning
Machine learning
Machine Learning
Metadata
microRNA
MicroRNAs
miRNA expressions
miRNAs
Missing value imputation
Model development
Predictive analytics
Proportional hazards
RNA
Stem cells
Support-vector machines
Survival prediction
survival rate
Survival Rate
Uterine Cervical Neoplasms
uterine cervix tumor
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