Survival time prediction by integrating cox proportional hazards network and distribution function network

Survival time prediction by integrating cox proportional hazards network and distribution function network

Background: The Cox proportional hazards model is commonly used to predict hazard ratio, which is the risk or probability of occurrence of an event of interest. However, the Cox proportional hazard model cannot directly generate an individual survival time. To do this, the survival analysis in the C...

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Bibliographic Details
Main Authors: Baek, E.-T (Author), Kang, S.-R (Author), Kim, S.H (Author), Lee, G.S (Author), Min, J.-J (Author), Oh, I.-J (Author), Yang, H.J (Author)
Format: Article
Language:English
Published: BioMed Central Ltd 2021
Subjects:
Activation mapping
article
Chemical activation
controlled study
Cox proportional hazard model
Cox proportional hazards models
Cox proportional hazards network
Data visualization
deep learning
Deep learning
Distribution function network
Distribution functions
Forecasting
Function evaluation
Hazards
heat
human
Log-normal distribution
methodology
Network activations
Normal distribution
prediction
probability
Probability
Probability of occurrence
prognosis
Prognosis
Proportional hazards
proportional hazards model
Proportional Hazards Models
Research Design
Specific distribution
survival analysis
Survival Analysis
survival time
Survival time prediction
Weibull distribution
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