Concepts (L)

Machine learning

Machine learning focuses on developing algorithms and models that enable computers to learn from and make predictions or decisions based on data without being explicitly programmed. In epidemiology, machine learning has several important uses and applications. This section is a very basic introduction to machine learning for Epidemiology.

Reading list

Key reference

Following ate optional but useful references

Video Lessons

Machine learning Reference
Machine learning Terminologies

What is included in this Video Lesson:

  • Reference 0:08
  • Types of Epidemiological models 0:32
  • Analyzing Epidemiological Study data 2:44
  • Machine learning 5:42
  • Terminologies 9:15
  • Classification of Machine learning 12:55
  • Classification of Supervised learning 17:30
  • Other classifications 18:42
  • Popular algorithms 20:06
  • Decision tree 20:50
  • Shrinkage Methods 26:37
  • Ensemble methods 37:04
  • Variable Importance measure 40:20
  • Epidemiologic applications 44:29
  • Future Reading 53:17

The timestamps are also included in the YouTube video description.

Video Lesson Slides

References

Bi, Qifang, Katherine E Goodman, Joshua Kaminsky, and Justin Lessler. 2019. “What Is Machine Learning? A Primer for the Epidemiologist.” American Journal of Epidemiology 188 (12): 2222–39.
James, Gareth, Daniela Witten, Trevor Hastie, and Robert Tibshirani. 2013. An Introduction to Statistical Learning. Vol. 112. Springer.
Karim, Ehsan. 2021. “Understanding Basics and Usage of Machine Learning in Medical Literature.” 2021. https://ehsanx.github.io/into2ML/.
Kuhn, Max, Kjell Johnson, Max Kuhn, and Kjell Johnson. 2013. “Over-Fitting and Model Tuning.” Applied Predictive Modeling, 61–92.
Liu, Yun, Po-Hsuan Cameron Chen, Jonathan Krause, and Lily Peng. 2019. “How to Read Articles That Use Machine Learning: Users’ Guides to the Medical Literature.” Jama 322 (18): 1806–16.
Steyerberg, Ewout W. 2019. Clinical Prediction Models: A Practical Approach to Development, Validation, and Updating. Vol. 2. Springer.
Vittinghoff, Eric, David V Glidden, Stephen C Shiboski, Charles E McCulloch, Eric Vittinghoff, David V Glidden, Stephen C Shiboski, and Charles E McCulloch. 2012. “Predictor Selection.” Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models, 395–429.