University of Eastern Finland
This repository systematizes the preliminary results of the isMODE project.
Currently, there are files with the source code and results presented in:
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the article "Epidemiological predictive modeling: lessons learned from the Kuopio Ischemic Heart Disease Risk Factor Study" by Christina Brester, Ari Voutilainen, Tomi-Pekka Tuomainen, Jussi Kauhanen, Mikko Kolehmainen
Figure 2 (an interactive version):
- AUC values in scenario 1: https://christinabrester.github.io/isMode/AUCs_scenario_1
Figure 3 (an interactive version):
- AUC values in scenario 2: https://christinabrester.github.io/isMode/AUCs_scenario_2
Additional tables with mean AUCs and 95%CI:
- scenario 1: https://christinabrester.github.io/isMode/CI_AUCs_scenario_1
- scenario 2: https://christinabrester.github.io/isMode/CI_AUCs_scenario_2
Source code: Jupyter notebook "model comparison.ipynb": https://github.com/christinabrester/isMode/blob/master/model%20comparison%20v2.ipynb
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the article "Post-analysis of predictive modeling with an epidemiological example" by Christina Brester, Ari Voutilainen, Tomi-Pekka Tuomainen, Jussi Kauhanen, Mikko Kolehmainen
Source code: Jupyter notebook "rule generation.ipynb": https://github.com/christinabrester/isMode/blob/master/rule%20generation.ipynb
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the article "Predicting risk of cardiovascular death on the high-dimensional electronic health record data in the presence of competing events" by Christina Brester, Ari Voutilainen, Tomi-Pekka Tuomainen, Jussi Kauhanen, Mikko Kolehmainen
Source code: Jupyter notebooks "1 - CIF vs KM.ipynb": https://github.com/christinabrester/isMode/blob/master/1%20-%20CIF%20vs%20KM.ipynb
"2 - Missing patters.ipynb": https://github.com/christinabrester/isMode/blob/master/2%20-%20Missing%20patters.ipynb
"3 - Data splitting into training, validation, test and filling gaps parts.ipynb": https://github.com/christinabrester/isMode/blob/master/3%20-%20Data%20splitting%20into%20training%2C%20validation%2C%20test%20and%20filling%20gaps%20parts.ipynb
"4 - Cause-specific and subdistribution hazard models, Random Forest for pre-selected predictors.ipynb": https://github.com/christinabrester/isMode/blob/master/4%20-%20Cause-specific%20and%20subdistribution%20hazard%20models%2C%20Random%20Forest%20for%20pre-selected%20predictors.ipynb
"5 - Random Forest for many predictors.ipynb": https://github.com/christinabrester/isMode/blob/master/5%20-%20Random%20Forest%20for%20many%20predictors.ipynb
"6 - AUC curves.ipynb": https://github.com/christinabrester/isMode/blob/master/6%20-%20AUC%20curves.ipynb