Focal loss added to an adversarial autoencoder improves sensitivity of Alzheimer's disease detection via normative modeling, but AUROC gains are inconsistent across datasets.
In: International conference on machine learning
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Normative Modeling for AD Diagnosis and Biomarker Identification
Focal loss added to an adversarial autoencoder improves sensitivity of Alzheimer's disease detection via normative modeling, but AUROC gains are inconsistent across datasets.