Abstract
Deep learning methods based on Convolutional Neural Networks (CNNs) have shown large potential to improve early and accurate diagnosis of Alzheimer's disease (AD) dementia based on imaging data. However, these methods have yet to be widely adopted in clinical practice, possibly due to the limited interpretability of deep learning models. The Explainable Boosting Machine (EBM) is a glass-box model but cannot learn features directly from input imaging data. In this study, we propose a novel interpretable model that combines CNNs and EBMs for the diagnosis and prediction of AD. We develop an innovative training strategy that alternatingly trains the CNN component as a feature extractor and the EBM component as the output block to form an end-to-end model. The model takes imaging data as input and provides both predictions and interpretable feature importance measures. We validated the proposed model on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, and the Health-RI Parelsnoer Neurode- generative Diseases Biobank (PND) as an external testing set. The proposed model achieved an area-under-the-curve (AUC) of 0.956 for AD and control classification, and 0.694 for the prediction of conversion of mild cognitive impairment (MCI) to AD on the ADNI cohort. The proposed model is a glass- box model that achieves a comparable performance with other state-of-the-art black-box models. Our code is available at: https://anonymous.4open.science/r/GL-ICNN.
Original language | English |
---|---|
Title of host publication | ISBI 2025 - 2025 IEEE 22nd International Symposium on Biomedical Imaging, Proceedings |
Publisher | IEEE Computer Society |
ISBN (Electronic) | 9798331520526 |
DOIs | |
Publication status | Published - 1 Jan 2025 |
Event | 22nd IEEE International Symposium on Biomedical Imaging - Houston, United States Duration: 14 Apr 2025 → 17 Apr 2025 Conference number: 22 https://biomedicalimaging.org/2025/ |
Publication series
Series | Proceedings - International Symposium on Biomedical Imaging |
---|---|
ISSN | 1945-7928 |
Conference
Conference | 22nd IEEE International Symposium on Biomedical Imaging |
---|---|
Abbreviated title | ISBI 2025 |
Country/Territory | United States |
City | Houston |
Period | 14/04/25 → 17/04/25 |
Internet address |
Keywords
- Alzheimer's disease
- Convolutional neural network
- Deep learning
- Explainable artificial intelligence
- Explainable boosting machine
- MRI