Developing Foundation Model for Early Detection of Alzheimer's Disease and Related Dementias (ADRD) from midlife

The superior performance of CNN is consistent with the literature and the relatively low validation loss demonstrates its generalisability. While this model is currently optimised for AD with limited features, a Transfer Learning paradigm is being employed to further train the CNN model to predict risk of other AD sub-types after including BioHermes dataset into pipeline. Future work will also explore modifications of the CNN architecture for multimodal features with explainability capabilities.