Alicia Gómez-Pascual, Talel Naccache, Jin Xu, Kourosh Hooshmand, Asger Wretlind, Martina Gabrielli, Marta Tiffany Lombardo, Liu Shi, Noel J Buckley, Betty M Tijms, Stephanie J B Vos, Mara Ten Kate, Sebastiaan Engelborghs, Kristel Sleegers, Giovanni B Frisoni, Anders Wallin, Alberto Lleó, Julius Popp, Pablo Martinez-Lage, Johannes Streffer, Frederik Barkhof, Henrik Zetterberg, Pieter Jelle Visser, Simon Lovestone, Lars Bertram, Alejo J Nevado-Holgado, Alice Gualerzi, Silvia Picciolini, Petroula Proitsi, Claudia Verderio, Juan A Botía, Cristina Legido-Quigley
BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative condition for which there is currently no available medication that can stop its progression. Previous studies suggest that mild cognitive impairment (MCI) is a phase that precedes the disease. Therefore, a better understanding of the molecular mechanisms behind MCI conversion to AD is needed. METHOD: Here, we propose a machine learning-based approach to detect the key metabolites and proteins involved in MCI progression to AD using data from the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery Study...
May 13, 2024: Computers in Biology and Medicine