2 citations · 3 across the 3 of their papers we have counts for
3 papers
eess.IV2023★ 1 cited
An Interpretable Machine Learning Model with Deep Learning-based Imaging Biomarkers for Diagnosis of Alzheimer's Disease
Wenjie Kang, Bo Li, Janne M. Papma +9
Machine learning methods have shown large potential for the automatic early diagnosis of Alzheimer's Disease (AD). However, some machine learning methods based on imaging data have…
eess.IV2020
Cross-Cohort Generalizability of Deep and Conventional Machine Learning for MRI-based Diagnosis and Prediction of Alzheimer's Disease
Esther E. Bron, Stefan Klein, Janne M. Papma +14
This work validates the generalizability of MRI-based classification of Alzheimer's disease (AD) patients and controls (CN) to an external data set and to the task of prediction of…
q-bio.NC2013★ 2 cited
A methodology for detecting and exploring non-convulsive seizures in patients with SAH
D J Albers, J Claassen, M J Schmidt +1
A methodology for understanding and de- tecting nonconvulsive seizures in individuals with sub- arachnoid hemorrhage is introduced. Specifically, begin- ning with an EEG signal, th…