Name
Title | ||
|---|---|---|
Predicting Pure Amnestic Mild Cognitive Impairment Conversion to Alzheimer's Disease Using Joint Modeling of Imaging and Clinical Data |
Abstract | ||
|---|---|---|
Predicting the conversion of amnestic mild cognitive impairment (aMCI) to Alzheimer's disease (AD) is a challenging problem for which machine learning could be of great use. In this work, we aim at assessing the independent and joint value of imaging (structural MRI, resting-state functional MRI (rsfMRI)) and clinical data in classifying stable versus progressive aMCI. Surprisingly, we found no previous studies using rsfMRI to predict conversion of MCI to AD. We use singular value decomposition as a feature extractor before combining modalities. We reach accuracies of up to 82% using rsfMRI, 86% using sMRI and rsfMRI combined, and 77% using a combination of all modalities. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/PRNI.2015.23 | PRNI |
Keywords | Field | DocType |
Alzheimer's disease, amnestic mild cognitive impairment, magnetic resonance imaging, machine learning, singular value decomposition | Modalities,Disease,Psychology,Speech recognition,Extractor,Cognitive impairment,Magnetic resonance imaging | Conference |
Citations | PageRank | References |
1 | 0.35 | 7 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| V. Kebets | 1 | 3 | 1.05 |
| Jonas Richiardi | 2 | 547 | 29.41 |
| M. van Assche | 3 | 1 | 0.35 |
| R. Goldstein | 4 | 1 | 0.35 |
| M. van der Meulen | 5 | 1 | 0.35 |
| P Vuilleumier | 6 | 435 | 40.82 |
| Dimitri Van De Ville | 7 | 1656 | 118.48 |
| Frédéric Assal | 8 | 7 | 1.23 |