Data Study Group Final Report: University College London Hospital - Morbidity Prediction Using Preoperative Cardiopulmonary Exercise Test Results

Data Study Groups are week-long events at The Alan Turing Institute bringing together some of the country’s top talent from data science, artificial intelligence, and wider fields, to analyse real-world data science challenges.

The purpose of this Data Study Group (DSG) was to apply modern machine learning techniques to develop models predicting postoperative morbidities from pre-surgery Cardiopulmonary Exercise Test (CPET) data. The DSG objectives included: creating models that are more predictive and interpretable than existing CPET-based risk models; comparing different machine learning algorithms in terms of predictive performance and interpretability; and using these models to derive additional predictive features from CPET data.

Data Study Group - September 2024 | The Alan Turing Institute