| layout | title |
|---|---|
page |
readings |
Boosted Trees for Risk Prognosis Alexis Bellot, Mihaela van der Schaar. Proceedings of the 3rd Machine Learning for Healthcare Conference, 2018
The Boosting Approach to Machine Learning An Overview Robert Schapire, Nonlinear Estimation and Classification, Springer, 2003
Clinical trials in acute myocardial infarction: should we adjust for baseline characteristics?
Ewout Steyerberg, Patrick Bossuyt, Kerry Lee. American Heart Journal, 2000
Illustrating Informed Presence Bias in Electronic Health Records Data: How Patient Interactions with a Health System Can Impact Inference
Matthew Phelan et al. The Journal for Electronic Health Data and Methods, 2017
An Introduction to Statistical Learning, Ch. 4: Classification
Daniela Witten et al. 2013
An introduction to variable and feature selection
Isabelle Guyon, Andre Elisseeff. Journal of Machine Learning Research, 2003
Logistic Regression: a brief primer
Jill Stoltzfus. Academic Emergency Medicine, 2011
Machine Learning in Medicine
Rahul Deo. Circulation, 2015
Machine Learning with Statistical Imputation for Predicting Drug Approvals
Andrew Lo, Kien Wei Siah, Chi Heem Wong. Harvard Data Science Review, 2019
Missing data imputation using statistical and machine learning methods in a real breast cancer problem
José Jerez el al. Artificial Intelligence in Medicine, 2010
Modern Clinical Text Mining: A Guide and Review
Bethany Percha, Annual Review of Biomedical Data Science, 2021
The Null Ritual: What you always wanted to know about significance testing but were afraid to ask
Gerd Gigerenzer et al. The Sage handbook of quantitative methodology for the social sciences, 2004
Opportunities and challenges in developing risk prediction models with electronic health records data: a systematic review
Benjamin Goldstein et al. JAMIA, 2016
Potential Biases in Machine Learning Algorithms Using Electronic Health Record Data
Milena Gianfrancesco et al. JAMA Internal Medicine, 2018
Random survival forests
Hemant Ishwaran et al. Annals of Applied Statistics 2008
Risk Prediction With Electronic Health Records: The Importance of Model Validation and Clinical Context
Benjamin Goldstein et al. JAMA Cardiology 2016
A short tutorial of GPower
Axel Buchner et al. Tutorials in quantitative methods for psychology, 2007
Statistical Modeling: The Two Cultures
Leo Breiman. Statistical Science, 2001
A Study of K-Nearest Neighbour as an Imputation Method
Gustavo Batista, Maria Carolina Monard. HIS, 2002
Using the ADAP Learning Algorithm to Forecast the Onset of Diabetes Mellitus
Jack Smith et al. Proceedings of the Annual Symposium on Computer Application in Medical Care, 1988
Why Doctors Hate Their Computers
Atul Gawande. The New Yorker, 2018
Why Most Published Research Findings Are False
John Ioannidis. PLoS medicine, 2005