Monday, 15 January 2024
9:00-10:30
Computer Lab 4A1 (Basement – Building U4).
Piazza della Scienza, 4 – 20126 Milano
Statistical boosting for prediction, advanced statistical modelling and clinical reality
Prof. Andreas Mayr
Department for Medical Biometry, Informatics and Epidemiology University of Bonn, Germany
Abstract
Biostatisticians nowadays can choose from a huge toolbox of advanced methods and algorithms for prediction purposes. Some of these tools are based on concepts from machine learning; other methods rely on more classical statistical modelling approaches. In the context of clinical prediction models, doctors are sometimes reluctant to consider risk scores that are constructed by black-box algorithms without clinically meaningful interpretation. Furthermore, even a both accurate and interpretable model will not often be used in practice, when it is based on variables that are difficult to obtain in clinical routine or when its calculation is too complex. In this talk, I will give a non-technical introduction to statistical boosting algorithms which can be interpreted as the methodological intersection between machine learning and statistical modelling. Boosting is able to perform variable selection while estimating statistical models from potentially high- dimensional data. It is mainly suitable for exploratory data analysis or prediction purposes. I will give an overview on some current methodological developments (including the development of polygenic risk scores) and provide an example for the construction of a clinical prediction model for post operative delirium with surprisingly simple solutions.
The link for attending the event on line:
https://uni-bonn.zoom-x.de/j/94447633434?pwd=UHVNVWFDSWZNbUY2NFBQS1ZGOWRVQT09
Meeting ID: 944 4763 3434 Password: 006662
For more information contact: fulvia.pennoni@unimib.it