Fig. 3: Schematic summary of the severe aortic stenosis research project. | npj Digital Medicine

Fig. 3: Schematic summary of the severe aortic stenosis research project.

From: Powering responsible artificial intelligence with high-quality real-world data: the S-RACE platform for scalable, multi-specialty clinical research

Fig. 3: Schematic summary of the severe aortic stenosis research project.The alternative text for this image may have been generated using AI.

Top left panel: overview of the ML analysis pipeline. The ML models are developed on the internal cohort using a nested cross validation. Nested cross validation was chosen because it provides an unbiased and more reliable estimate of a model’s true performance by separating hyperparameter tuning from final evaluation, preventing data leakage and promoting robust generalisation compared to standard cross validation. Following a similar approach of the kidney cancer research project, the best performing model is then re-trained on all the internal cohort and then externally validated. Top right panel: application of the responsible AI error decision tree. Based on the features included in the final model, a decision tree is trained to optimise the split among subpopulations with the highest / lowest number of erroneous classifications.

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