Skip to content

Exploring the Supervised Learning Models to Automatically Diagnose Colon Cancer Patients based on their SNP Profiles

Notifications You must be signed in to change notification settings

alibrahimzada/Colon-Cancer

Repository files navigation

Colon-Cancer

Exploring the Supervised Learning Models to Automatically Diagnose Colon Cancer Patients based on their SNP Profiles - Predicting the Predisposition to Colorectal Cancer based on SNP Profiles of Immune Checkpoints using Supervised Learning Models. 7th International Congress of Molecular Medicine, Istanbul / Turkey.

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 to improve public health.

Access Conference Publication
Access Full Text

About

Exploring the Supervised Learning Models to Automatically Diagnose Colon Cancer Patients based on their SNP Profiles

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages