Information Systems Faculty Publications and Presentations

Document Type

Conference Proceeding

Publication Date



Neurological diseases, including Alzheimer's disease (AD), are rising global health challenges. This study presents a two-stage decision support system (DSS) that uses machine learning and neuroimaging for early AD detection and monitoring. The first stage uses deep learning for predicting AD likelihood. The second leverages a 3D convolutional neural network to identify crucial brain regions in AD progression. Notably, the DSS offers a solution to machine learning's "black box" problem using an occlusion map explainability method, enhancing decision transparency. Its design is adaptable to other diseases using imaging data, underscoring its broad healthcare potential. By providing an innovative and interpretable tool for improved disease management, this research helps foster better patient care and outcomes.


Attribution-NonCommercial-NoDerivatives 4.0 International

Publication Title

Proceedings of the 57th Hawaii International Conference on System Sciences

Included in

Business Commons



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