Description

Deep learning models trained on MRI brain scans of healthy subjects can be used to predict age. Accurate estimation of brain age is important for reliably detecting abnormal aging in the brain. One way to increase the performance of predicted brain age is through using multimodal data. Previous research using multimodal data has largely been non-deep learning-based; in this, we examine a deep learning model that can effectively utilize several modalities. We found that using multimodal data reduced the mean absolute error of predicted ages.