Resources for learning Machine Learning to create clinical predictive models.
1
1
Entering edit mode
8 weeks ago
egascon ▴ 60

Hello

I am writing to ask if you know of any resources and tutorials to learn how to create predictive models to validate genes as potential biomarkers and make survival predictions.

I have been reading several papers and many of them apply techniques such as the Lasso algorithm, SMV, Random Forest, ROC curves... etc. I understand the theory but I am struggling to find a step-by-step guide to perform these analyses.

An example workflow that I would really like to learn is the following: enter link description here

What learning resources do you recommend? (Besides the Biostars book, which I want to buy as well)

Thank you very much for your help.

Machine-Learning AI • 341 views
ADD COMMENT
1
Entering edit mode
8 weeks ago
Jeremy ▴ 930

There are a couple of statistics books that use R that might help you. "Statistics: An Introduction Using R" by Crawley has a short chapter on death and failure data. "An Introduction to Statistical Learning with Applications in R" by James et al. has a more detailed chapter on survival analysis and censored data. (It looks like there's also a Python version of this book available now.) The downside is that each book costs about $30 (at least on Amazon).

You could also look for notebooks on biomarkers and/or survival analysis on Kaggle. I would pay special attention to notebooks made by masters and grandmasters (with a red or yellow circle around their profile picture). For example, here's a Kaggle Python notebook on pancreatic cancer that you might find useful:

Predicting Pancreatic Cancer

You can also check out Kevin Blighe's Biostars tutorial here:

Survival Analysis

ADD COMMENT

Login before adding your answer.

Traffic: 1976 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6