Assessment of corticospinal tract dysfunction and disease severity in\n amyotrophic lateral sclerosis

2016/09/28 by Rahul Remanan, Viktor Sukhotskiy, Remanan, Rahul +7
Medicine · Neuroscience · #Amyotrophic Lateral Sclerosis Research #FOS: Biological sciences #Neurological disorders and treatments #Neurons and Cognition (q-bio.NC) #Neuroscience and Neural Engineering #Parkinson's Disease Mechanisms and Treatments #Tissues and Organs (q-bio.TO)

paper · pdf · doi:10.48550/arxiv.1609.08980

openalex publication_date 2016/09/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

The upper motor neuron dysfunction in amyotrophic lateral sclerosis was\nquantified using triple stimulation and more focal transcranial magnetic\nstimulation techniques that were developed to reduce recording variability.\nThese measurements were combined with clinical and neurophysiological data to\ndevelop a novel random forest based supervised machine learning prediction\nmodel. This model was capable of predicting cross-sectional ALS disease\nseverity as measured by the ALSFRSr scale with 97% overall accuracy and 99%\nprecision. The machine learning model developed in this research provides a\nnew, unique and objective diagnostic method for quantifying disease severity\nand identifying subtle changes in disease progression in ALS.\n

Citations

• A comparison of random forest regression and multiple linear regression for prediction in neuroscience

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