We study the problem of classifying mild Alzheimer's disease (AD) subjects from healthy individuals (controls) using multi-modal image data, to facilitate ...
We study the problem of classifying mild Alzheimer's disease (AD) subjects from healthy individuals (controls) using multi-modal image data, to facilitate ...
This paper explores the AD classification problem using multiple modalities simultaneously. The difficulty here is to assess the relevance of each modality ( ...
We study the problem of classifying mild Alzheimer's disease (AD) subjects from healthy individuals (controls) using <em>multi-modal</em> image data, ...
We study the problem of classifying mild Alzheimer's disease (AD) subjects from healthy individuals (controls) using multi-modal image data, to facilitate ...
MKL for robust multi-modality AD classification. scientific article published on 01 January 2009. In more languages. Spanish. No label defined. artículo ...
Hinrichs et al. (2009) use Multiple Kernel Learning (MKL) to fuse multi-modality data by learning an optimal linearly combined kernels for classification. ...
Jan 20, 2024 · The study presents an innovative diagnostic framework that synergises Convolutional Neural Networks (CNNs) with a Multi-feature Kernel ...
Missing: MKL | Show results with:MKL
MKL for Robust Multi-modality AD Classification · Alzheimer's disease diagnosis in individual subjects using structural MR images: Validation studies · Computer- ...
Our method is based on the Multi-Kernel Learning (MKL) framework, which allows the inclusion of an arbitrary number of views of the data in a maximum margin, ...
Missing: Robust | Show results with:Robust