Available at https://link.springer.com/chapter/10.1007/978-3-030-67051-1_4
Cite : Mondal, S., Bhattacharya, N., Das, T., Ghosh, Z., & Khatua, S. (2021). Implication of Statistical Methods on Patient Data: An Approach for Cancer Survivability Prediction. In Intelligent Healthcare (pp. 57-80). Springer, Cham.
Prerequisites :
The required dependencies for the analysis is R programming R version >= 3.6
and is tested to work under windows as well as Ubuntu.
Dataset preparation
breast.txt and ovary.txt is the input files for the analysis.
We have preprocessed the original data and initialized some labels according to the category.
Label for Breast & Ovarian cancer data:
Ethnicity:
white =0
black or african american =1
asian=2
Status: 1 =alive, 2=dead
Stage:
stage:i=0, stage:ia=0, stage:ib=0
stage:iia=1, stage:iib=1
stage:iiia=2, stage:iiib=2, stage:iiic=2
stage:iv=3
BRCA1 avg FPKM 2.48 low FPKM =1 BRCA1 High=2
BRCA2 avg FPKM 1.03 low FPKM =1 BRCA1 High=2
ATM avg FPKM 2.43 low FPKM =1 BRCA1 High=2
To start a run :
Breast_KM.R & Ovary_KM.R for Kaplan-Meier
breast_cox.R & ovary_Cox.R for Cox PH
Feedback
Any further information contact at
smcse_rs@caluniv.ac.in, namrata.bhattacharya03@gmail.com, dastroyee1993@gmail.com