PRedicting the EVolution of SubjectIvE Cognitive Decline to Alzheimer's Disease With machine learnin...
PRedicting the EVolution of SubjectIvE Cognitive Decline to Alzheimer's Disease With machine learning: the PREVIEW study protocol
About this item
Full title
Author / Creator
Mazzeo, Salvatore , Lassi, Michael , Padiglioni, Sonia , Vergani, Alberto Arturo , Moschini, Valentina , Scarpino, Maenia , Giacomucci, Giulia , Burali, Rachele , Morinelli, Carmen , Fabbiani, Carlo , Galdo, Giulia , Amato, Lorenzo Gaetano , Bagnoli, Silvia , Emiliani, Filippo , Ingannato, Assunta , Nacmias, Benedetta , Sorbi, Sandro , Grippo, Antonello , Mazzoni, Alberto and Bessi, Valentina
Publisher
England: BioMed Central Ltd
Journal title
Language
English
Formats
Publication information
Publisher
England: BioMed Central Ltd
Subjects
More information
Scope and Contents
Contents
As disease-modifying therapies (DMTs) for Alzheimer's disease (AD) are becoming a reality, there is an urgent need to select cost-effective tools that can accurately identify patients in the earliest stages of the disease. Subjective Cognitive Decline (SCD) is a condition in which individuals complain of cognitive decline with normal performances o...
Alternative Titles
Full title
PRedicting the EVolution of SubjectIvE Cognitive Decline to Alzheimer's Disease With machine learning: the PREVIEW study protocol
Authors, Artists and Contributors
Author / Creator
Lassi, Michael
Padiglioni, Sonia
Vergani, Alberto Arturo
Moschini, Valentina
Scarpino, Maenia
Giacomucci, Giulia
Burali, Rachele
Morinelli, Carmen
Fabbiani, Carlo
Galdo, Giulia
Amato, Lorenzo Gaetano
Bagnoli, Silvia
Emiliani, Filippo
Ingannato, Assunta
Nacmias, Benedetta
Sorbi, Sandro
Grippo, Antonello
Mazzoni, Alberto
Bessi, Valentina
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_7ef94172f33649e486e42d3ec56c858b
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_7ef94172f33649e486e42d3ec56c858b
Other Identifiers
ISSN
1471-2377
E-ISSN
1471-2377
DOI
10.1186/s12883-023-03347-8
