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Constructing personalized characterizations of structural brain aberrations in patients with dementia using explainable artificial intelligence | npj Digital Medicine

Nature
We trained convolutional neural networks on structural brain scans to differentiate dementia patients from healthy controls, and applied layerwise relevance...
5 months ago

Explained predictions of strong eastern Pacific El Niño events using deep learning | Scientific Reports

Nature
Global and regional impacts of El Niño-Southern Oscillation (ENSO) are sensitive to the details of the pattern of anomalous ocean warming...
10 months ago

Layer-Wise Relevance Propagation for Explaining Deep Neural Network Decisions in MRI-Based Alzheimer's Disease Classification

Frontiers
In this study, we propose using layer-wise relevance propagation (LRP) to visualize convolutional neural network decisions for AD based on MRI data.
3 months ago

Explainable machine learning in cybersecurity: A survey - Yan - 2022 - International Journal of Intelligent Systems

Wiley Online Library
In this paper, we present the topic of explainable ML in cybersecurity through two general types of explanations: (1) ante hoc explanation, and (2) post hoc...
23 months ago

Explainable AI: A review of applications to neuroimaging data

Frontiers
Deep neural networks (DNNs) have transformed the field of computer vision and currently constitute some of the best models for representations learned via...
8 months ago

From attribution maps to human-understandable explanations through Concept Relevance Propagation

Nature
CRP is an extension of LRP, which disentangles the relevance flows associated with concepts learned by the model via conditional backpropagation.
12 months ago

Explainable artificial intelligence for searching frequency characteristics in Parkinson¡¯s disease tremor

Nature
This new classification method reconstructs the neural network's original function, achieving a 73% PD and ET tremor classification accuracy.
11 months ago

Explainable sequence-to-sequence GRU neural network for pollution forecasting

Nature
In this work, we extend the LRP technique to a sequence-to-sequence neural network model with GRU layers.
15 months ago

Interpretable deep learning for the remote characterisation of ambulation in multiple sclerosis using smartphones

Nature
Deep Convolutional Neural Networks (DCNN) may capture a richer representation of healthy and MS-related ambulatory characteristics from the raw smartphone-...
39 months ago

Tens of images can suffice to train neural networks for malignant leukocyte detection

Nature
Convolutional neural networks (CNNs) excel as powerful tools for biomedical image classification. It is commonly assumed that training CNNs...
42 months ago