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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...
6 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...
11 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...
24 months ago
| LIME: Explaining individual predictions in the medical context (Ribeiro et al., 2016).
ResearchGate
Increasing quality and performance of artificial intelligence (AI) in general and machine learning (ML) in particular is followed by a wider use of these...
23 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.
13 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-...
40 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.
16 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...
43 months ago
Data-driven identification of diagnostically useful extrastriatal signal in dopamine transporter SPECT using explainable AI
Nature
This study used explainable artificial intelligence for data-driven identification of extrastriatal brain regions that can contribute to the interpretation of...
35 months ago