Our manuscript “Improving 3D convolutional neural network comprehensibility via interactive visualization of relevance maps: Evaluation in Alzheimer’s disease” has been published by the renowned Journal Alzheimer’s Research & Therapy (Impact Factor: 6.981).
It describes the modeling strategy and neural network training, extensive model validation using three independent samples, and visualization of relevance maps to support the comprehensibility of the model’s decision.
The journal article is freely available on BioMed Central (BMC) under open access license.
