Problem Description

The goal of the IFMBE Scientific Challenge 2022 was to capture the patterns of user acquisitions using the measurements of an Active and Healthy Ageing (AHA) mobile application to identify early dropouts. More precisely, given a window of consecutive scheduled acquisitions, along with other user static features, such as demographic characteristics, the objective is to predict the user’s adherence for the following three future acquisitions.

Participation

Our team won the first place in the IFMBE Scientific Challenge 2022 using machine learning and oversampling techniques. The corresponding publication entitled “Predicting Early Dropouts of an Active and Healthy Ageing App” has been presented in the IUPESM World Congress on Medical Physics and Biomedical Engineering 2022, held in June 12-17, 2022.

There were more than 20 competing teams and the ranking of the three finalists is given below:

Watch the IFMBE Scientific Challenge Awards Ceremony

Watch the IFMBE Scientific Challenge Presentations Session