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Jan 20

ARTIFICIAL INTELLIGENCE AND NEUROPSYCHOLOGICAL MEASURES: THE CASE OF ALZHEIMER’S DISEASE [publication pdf] [publication website]

AUTHORS: Battista, P., Salvatore, C., Berlingeri, M., Cerasa, A., & Castiglioni, I. 

JOURNAL: Neuroscience & Biobehavioral Reviews

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Jan 20

COMPARISON OF TRANSFER LEARNING AND CONVENTIONAL MACHINE LEARNING APPLIED TO STRUCTURAL BRAIN MRI FOR THE EARLY DIAGNOSIS AND PROGNOSIS OF ALZHEIMER'S DISEASE [publication pdf] [publication website]

AUTHORS: Nanni, L., Interlenghi, M., Brahnam, S., Salvatore, C., Papa, S., Nemni, R., ... & Alzheimer's Disease Neuroimaging Initiative

JOURNAL: Frontiers in neurology

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Jan 19

TEXTURE DESCRIPTORS AND VOXELS FOR THE EARLY DIAGNOSIS OF ALZHEIMER'S DISEASE

Nanni, L., Brahnam, S., Salvatore, C., Castiglioni, I., & Alzheimer's Disease Neuroimaging Initiative. (2019). Texture descriptors and voxels for the early diagnosis of Alzheimer’s disease. Artificial Intelligence in Medicine, 97, 19–26. https://doi.org/10.1016/j.artmed.2019.05.003

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Jan 18

MRI CHARACTERIZES THE PROGRESSIVE COURSE OF AD AND PREDICTS CONVERSION TO ALZHEIMER'S DEMENTIA 24 MONTHS BEFORE PROBABLE DIAGNOSIS

Salvatore, C., Cerasa, A., & Castiglioni, I. (2018). MRI characterizes the progressive course of AD and predicts conversion to Alzheimer’s dementia 24 months before probable diagnosis. Frontiers in Aging Neuroscience, 10, 135. https://doi.org/10.3389/fnagi.2018.00135

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Jan 18

A WRAPPED MULTI-LABEL CLASSIFIER FOR THE AUTOMATIC DIAGNOSIS AND PROGNOSIS OF ALZHEIMER'S DISEASE

Salvatore, C., & Castiglioni, I. (2018). A wrapped multi-label classifier for the automatic diagnosis and prognosis of Alzheimer’s disease. Journal of Neuroscience Methods, 302, 14–23. https://doi.org/10.1016/j.jneumeth.2017.12.016

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Jan 17

OPTIMIZING NEUROPSYCHOLOGICAL ASSESSMENTS FOR COGNITIVE, BEHAVIORAL, AND FUNCTIONAL IMPAIRMENT CLASSIFICATION: A MACHINE LEARNING STUDY

Battista, P., Salvatore, C., & Castiglioni, I. (2017). Optimizing neuropsychological assessments for cognitive, behavioral, and functional impairment classification: A machine learning study. Behavioural Neurology, 2017, Article ID 1850909. https://doi.org/10.1155/2017/1850909

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Jan 16

COMBINING MULTIPLE APPROACHES FOR THE EARLY DIAGNOSIS OF ALZHEIMER'S DISEASE

Nanni, L., Salvatore, C., Cerasa, A., Castiglioni, I., & Alzheimer's Disease Neuroimaging Initiative. (2016). Combining multiple approaches for the early diagnosis of Alzheimer’s disease. Pattern Recognition Letters, 84, 259–266. https://doi.org/10.1016/j.patrec.2016.10.010

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Jan 16

FRONTIERS FOR THE EARLY DIAGNOSIS OF AD BY MEANS OF MRI BRAIN IMAGING AND SUPPORT VECTOR MACHINES

Salvatore, C., Battista, P., & Castiglioni, I. (2016). Frontiers for the early diagnosis of AD by means of MRI brain imaging and support vector machines. Current Alzheimer Research, 13(5), 509–533. https://doi.org/10.2174/1567205013666151116141705

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Jan 15

MAGNETIC RESONANCE IMAGING BIOMARKERS FOR THE EARLY DIAGNOSIS OF ALZHEIMER'S DISEASE: A MACHINE LEARNING APPROACH

Salvatore, C., Cerasa, A., Battista, P., Gilardi, M. C., Quattrone, A., & Castiglioni, I. (2015). Magnetic resonance imaging biomarkers for the early diagnosis of Alzheimer’s disease: A machine learning approach. Frontiers in Neuroscience, 9, 307. https://doi.org/10.3389/fnins.2015.00307