Paper by Maria Athanasiou, Konstantina Sfrintzeri, Konstantia Zarkogianni, Anastasia Thanopoulou, and Konstantina Nikita receives the Best Student Paper Award in IEEE BIBE 2020
A paper entitled “An Explainable XGBoost-Based Approach Towards Assessing the Risk of Cardiovascular Disease in Patients with Type 2 Diabetes Mellitus” was presented on October 28, 2020, in the [20th IEEE International Conference on BioInformatics And BioEngineering (BIBE)](https://www.ieeebibe2020.org/), and received the Best Student Paper Award. The paper proposes an explainable personalized risk prediction model for the fatal or non-fatal CVD incidence in individuals with Type 2 Diabetes. An explainable approach based on the eXtreme Gradient Boosting (XGBoost) and the Tree SHAP (SHapley Additive exPlanations) method is deployed for the calculation of the 5-year CVD risk and the generation of individual explanations on the model’s decisions. Data from the 5- year follow up of 560 patients with T2DM are used for development and evaluation purposes. The obtained results (AUC=71.13%) indicate the potential of the proposed approach to handle the unbalanced nature of the used dataset, while providing clinically meaningful insights about the model’s decision process.
To find out more, please check out the paper presentation and the full paper.