A supervised method to assist the diagnosis and monitor progression of Alzheimer's disease using data from an fMRI experiment

• Published in: Artificial intelligence in medicine Vol. 53; no. 1; pp. 35 - 45
• Main Authors: Tripoliti, Evanthia E., Fotiadis, Dimitrios I., Argyropoulou, Maria
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.09.2011
• Subjects: Adolescent; Aged; Aged, 80 and over; Algorithms; Alzheimer Disease - diagnosis; Alzheimer Disease - pathology; Alzheimer's disease; Disease Progression; Female; Functional magnetic resonance imaging; Generalized linear model; Humans; Image Interpretation, Computer-Assisted - methods; Image Processing, Computer-Assisted - methods; Internal Medicine; Magnetic Resonance Imaging - methods; Male; Other; Random forests; Young Adult; Functional magnetic resonance imaging; Generalized linear model; Alzheimer's disease; Random forests

► We propose a supervised method to assist the diagnosis, and monitor the progression of Alzheimer's disease. ► It is fully automated, and independent from the type of the fMRI experiment and the type of the task. ► It is based on features extracted from an fMRI experiment. ► It fuses features...