Motor neuron disease is an umbrella term encompassing a multitude of clinically
heterogeneous phenotypes. The early and accurate categorisation of patients is hugely …

Although machine-learning (ML) approaches have been extensively utilized in
neurodegenerative conditions, they can be challenging to implement in motor neuron …

Objectives To stratify patients with multiple sclerosis (pwMS) based on brain MRI-derived
volumetric features using unsupervised machine learning. Methods The 3-T brain MRIs of …

Diagnosis, stratification and monitoring of disease progression in amyotrophic lateral
sclerosis currently rely on clinical history and examination. The phenotypic heterogeneity of …

This prospective study developed an MRI-based method for identification of individual motor
neuron disease (MND) patients and test its accuracy at the individual patient level in an …

The potential of multiparametric quantitative neuroimaging has been extensively discussed
as a diagnostic tool in amyotrophic lateral sclerosis (ALS). In the past, the integration of …

Objectives To evaluate the accuracy of a data-driven approach, such as machine learning
classification, in predicting disability progression in MS. Methods We analyzed structural …

Timely diagnosis and accurate phenotyping of amyotrophic lateral sclerosis (ALS) is of
paramount importance for the clinical management of patients. Magnetic Resonance …

Background Despite significant advances in quantitative neuroimaging, the diagnosis of
ALS remains clinical and MRI-based biomarkers are not currently used to aid the diagnosis …

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease whose diagnosis
depends on the presence of combined lower motor neuron (LMN) and upper motor neuron …