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Convolutional neural network based prediction of conversion from mild cognitive impairment to alzheimer's disease: A technique using hippocampus extracted from …
G Mukhtar, S Farhan - Advances in Electrical and Computer …, 2020 - search.proquest.com
Alzheimer's disease (AD) is an irreversible neurodegenerative disorder. Mild Cognitive
Impairment (MCI) is a prodromal stage of AD and its identification is very crucial for early …
Impairment (MCI) is a prodromal stage of AD and its identification is very crucial for early …
Targeting the uncertainty of predictions at patient-level using an ensemble of classifiers coupled with calibration methods, Venn-ABERS, and Conformal Predictors: a …
Despite being able to make accurate predictions, most existing prognostic models lack a
proper indication about the uncertainty of each prediction, that is, the risk of prediction error …
proper indication about the uncertainty of each prediction, that is, the risk of prediction error …
Meta-weighted gaussian process experts for personalized forecasting of AD cognitive changes
We introduce a novel personalized Gaussian Process Experts (pGPE) model for predicting
per-subject ADAS-Cog13 cognitive scores–a significant predictor of Alzheimer's Disease …
per-subject ADAS-Cog13 cognitive scores–a significant predictor of Alzheimer's Disease …
Personalized gaussian processes for forecasting of alzheimer's disease assessment scale-cognition sub-scale (adas-cog13)
In this paper, we introduce the use of a personalized Gaussian Process pGP model to
predict per-patient changes in ADAS-Cog13-a significant predictor of Alzheimer's Disease …
predict per-patient changes in ADAS-Cog13-a significant predictor of Alzheimer's Disease …
Ensemble learning with Conformal Predictors: Targeting credible predictions of conversion from Mild Cognitive Impairment to Alzheimer's Disease
T Pereira, S Cardoso, D Silva, M Guerreiro… - arxiv preprint arxiv …, 2018 - arxiv.org
Most machine learning classifiers give predictions for new examples accurately, yet without
indicating how trustworthy predictions are. In the medical domain, this hampers their …
indicating how trustworthy predictions are. In the medical domain, this hampers their …