TY  - JOUR
AU  - Hernández Lorenzo, Laura
AU  - Gil‐Moreno, Maria José
AU  - Ortega‐Madueño, Isabel
AU  - Cárdenas Fernández, María Cruz
AU  - Diez‐Cirarda, María
AU  - Delgado Álvarez, Alfonso
AU  - Palacios‐Sarmiento, Marta
AU  - Matías-Guiu Guía, Jorge
AU  - Corrochano Sánchez, Silvia
AU  - Ayala Rodrigo, José Luis
AU  - Matias‐Guiu Antem, Jordi
PY  - 2023
DO  - 10.1111/cns.14382
SN  - 1755-5930
UR  - https://hdl.handle.net/20.500.14352/99840
T2  - CNS Neuroscience and Therapeutics
AB  - Aims: The AT(N) classification system not only improved the biological characteriza-tion of Alzheimer's disease (AD) but also raised challenges for its clinical application. Unbiased, data-driven techniques such as clustering may help optimize it,...
LA  - eng
PB  - Wiley Open Access
KW  - Alzheimer's disease
KW  - Cerebrospinal fluid
KW  - Clustering analysis
KW  - Early detection
KW  - Machine learning
KW  - Mild cognitive impairment
TI  - A data-driven approach to complement the A/T/(N) classification system using CSF biomarkers
TY  - journal article
ER  -