Matrix-similarity based loss function and feature selection for Alzheimer's disease diagnosis

Keyphrases

• Loss Function 100%
• Alzheimer's Disease Diagnosis 100%
• Feature Selection 100%
• Similarity-based 100%
• Similarity Matrix 100%
• Functional Selection 100%
• Disease Status 60%
• Mild Cognitive Impairment 40%
• Alzheimer's Disease 40%
• Response Matrix 40%
• Status Identification 40%
• Clinical Prediction Score 40%
• Alzheime's Disease 40%
• Alzheimer's Disease Neuroimaging Initiative 20%
• State-of-the-art Techniques 20%
• Clinical Score 20%
• Response Predictors 20%
• Target Response 20%
• Score-based 20%
• Brain Diseases 20%
• High-level Information 20%
• Novel Matrix 20%
• Joint Feature Selection 20%
• LASSO Algorithm 20%
• Joint Regression 20%
• Prodromal Stage 20%
• Least Absolute Shrinkage and Selection Operator (LASSO) 20%
• Neuroimaging Features 20%
• Joint Classification 20%

Computer Science

• Feature Selection 100%
• Similarity Matrix 100%
• Feature Extraction 100%
• Brain Disease 33%

Biochemistry, Genetics and Molecular Biology

• Feature Extraction 100%