Predicting the Survival Time for Bladder Cancer Using an Additive Hazards Model in Microarray Data
Background: One substantial part of microarray studies is to predict patients' survival based on their gene expression profile. Variable selection techniques are powerful tools to handle high dimensionality in analysis of microarray data. However, these techniques have not been investigated in...
Saved in:
Main Authors: | Leili TAPAK (Author), Hossein MAHJUB (Author), Majid SADEGHIFAR (Author), Massoud SAIDIJAM (Author), Jalal POOROLAJAL (Author) |
---|---|
Format: | Book |
Published: |
Tehran University of Medical Sciences,
2016-02-01T00:00:00Z.
|
Subjects: | |
Online Access: | Connect to this object online. |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Landmark Prediction of Survival for Breast Cancer Patients: A Case Study in Tehran, Iran
by: Behnaz ALAFCHI, et al.
Published: (2019) -
Identifying Important Risk Factors for Survival in Kidney Graft Failure Patients Using Random Survival Forests
by: Omid HAMIDI, et al.
Published: (2016) -
Model-based Recursive Partitioning for Survival of Iranian Female Breast Cancer Patients: Comparing with Parametric Survival Models
by: Mozhgan SAFE, et al.
Published: (2017) -
A Gene Selection Method for Survival Prediction in Diffuse Large B-Cell Lymphomas Patients using 1D Discrete Wavelet Transform.
by: Maryam Farhadian, et al.
Published: (2014) -
Predicting preeclampsia and related risk factors using data mining approaches: A cross-sectional study
by: Zohreh Manoochehri, et al.
Published: (2021)