Related Experiment Video
Updated: Feb 5, 2026

Asthma Detection Research Based on Voice Signal Processing and Machine Learning
Published on: July 22, 2025
Structural neuroimaging as clinical predictor: A review of machine learning applications
José María Mateos-Pérez1, Mahsa Dadar1, María Lacalle-Aurioles1
1Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.
Abstract:
In this paper, we provide an extensive overview of machine learning techniques applied to structural magnetic resonance imaging (MRI) data to obtain clinical classifiers. We specifically address practical problems commonly encountered in the literature, with the aim of helping researchers improve the application of these techniques in future works. Additionally, we survey how these algorithms are applied to a wide range of diseases and disorders (e.g. Alzheimer's disease (AD), Parkinson's disease (PD), autism, multiple sclerosis, traumatic brain injury, etc.) in order to provide a comprehensive view of the state of the art in different fields.
Related Concept Videos
Clinical Applications of Epidermal Stem Cells
Review and Preview
Percentiles are a type of fractile that partition data into...
Review and Preview
Local Anesthetics: Clinical Application as Spinal Anesthesia
Local Anesthetics: Clinical Application as Epidural Anesthesia
Since epidural anesthetics can be infused through an epidural catheter, all types of drugs, including short-acting ones, can be administered. Chloroprocaine and lidocaine are examples of short and long-duration anesthetics, respectively. Bupivacaine...
Machines
A free-body diagram of the...

