Skip to content

The goal of this analysis is to explore the machine learning-based automatic diagnosis of colorectal patients based on the single nucleotide polymorphisms (SNP). Such a computational approach may be used complementary to other diagnosis tools, such as, biopsy, CT scan, and MRI. Moreover, it may be used as a low-cost screening for colorectal cancers

Notifications You must be signed in to change notification settings

HuzeyfeAyaz/CRC_Prediction_with_Immune_SNP_Profiles

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

2 Commits
 
 
 
 
 
 
 
 

Repository files navigation

Predicting the Predisposition to Colorectal Cancer based on SNP Profiles of Immune Phenotypes using Supervised Learning Models. Medical & Biological Engineering & Computing

Cite

If you are using CRC Prediction on academic studies cite the following paper:

Cakmak, A., Ibrahimzada A. R., Arıkan, S., Ayaz, H., Demirkol, Ş., Sönmez, D., Hakan, M. T., Turan, S. S., Horozoğlu, C., Küçükhüseyin, Ö., Kiran, B., Zeybek, Ş. Ü., Baysan, M., Yaylim, I. (2022). Predicting the Predisposition to Colorectal Cancer based on SNP Profiles of Immune Phenotypes using Supervised Learning Models. Medical & Biological Engineering & Computing, DOI: 10.1007/s11517-022-02707-9.

About

The goal of this analysis is to explore the machine learning-based automatic diagnosis of colorectal patients based on the single nucleotide polymorphisms (SNP). Such a computational approach may be used complementary to other diagnosis tools, such as, biopsy, CT scan, and MRI. Moreover, it may be used as a low-cost screening for colorectal cancers

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 99.1%
  • Python 0.9%