AIMC Topic: Amyotrophic Lateral Sclerosis

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eyeSay: Brain Visual Dynamics Decoding With Deep Learning & Edge Computing.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Brain visual dynamics encode rich functional and biological patterns of the neural system, and if decoded, are of great promise for many applications such as intention understanding, cognitive load quantization and neural disorder measurement. We her...

Robot-assisted training using hybrid assistive limb ameliorates gait ability in patients with amyotrophic lateral sclerosis.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
OBJECTIVE: The Hybrid Assistive Limb (HAL; CYBERDYNE, Inc., Japan) is a wearable robot device that provides effective gait assistance according to voluntary intention by detecting weak bioelectrical signals of neuromuscular activity on the surface of...

Image-based deep learning reveals the responses of human motor neurons to stress and VCP-related ALS.

Neuropathology and applied neurobiology
AIMS: Although morphological attributes of cells and their substructures are recognised readouts of physiological or pathophysiological states, these have been relatively understudied in amyotrophic lateral sclerosis (ALS) research.

Classification of amyotrophic lateral sclerosis by brain volume, connectivity, and network dynamics.

Human brain mapping
Emerging studies corroborate the importance of neuroimaging biomarkers and machine learning to improve diagnostic classification of amyotrophic lateral sclerosis (ALS). While most studies focus on structural data, recent studies assessing functional ...

Ropinirole involved in a fatal case: blood and urinary concentrations.

Forensic toxicology
PURPOSE: Ropinirole is an antiparkinsonian  drug and has recently been suggested to be effective in amyotrophic lateral sclerosis. It is expected that ropinirole prescriptions will increase in the near future. However, the fatal concentration in bloo...

The Emerging Role of Long Non-Coding RNAs and MicroRNAs in Neurodegenerative Diseases: A Perspective of Machine Learning.

Biomolecules
Neurodegenerative diseases (NDs) are characterized by progressive neuronal dysfunction and death of brain cells population. As the early manifestations of NDs are similar, their symptoms are difficult to distinguish, making the timely detection and d...

Biomedical signals and machine learning in amyotrophic lateral sclerosis: a systematic review.

Biomedical engineering online
INTRODUCTION: The use of machine learning (ML) techniques in healthcare encompasses an emerging concept that envisages vast contributions to the tackling of rare diseases. In this scenario, amyotrophic lateral sclerosis (ALS) involves complexities th...

Prediction of caregiver quality of life in amyotrophic lateral sclerosis using explainable machine learning.

Scientific reports
Amyotrophic Lateral Sclerosis (ALS) is a rare neurodegenerative, fatal and currently incurable disease. People with ALS need support from informal caregivers due to the motor and cognitive decline caused by the disease. This study aims to identify ca...

Artificial intelligence in neurodegenerative diseases: A review of available tools with a focus on machine learning techniques.

Artificial intelligence in medicine
Neurodegenerative diseases have shown an increasing incidence in the older population in recent years. A significant amount of research has been conducted to characterize these diseases. Computational methods, and particularly machine learning techni...

Prediction Model of Amyotrophic Lateral Sclerosis by Deep Learning with Patient Induced Pluripotent Stem Cells.

Annals of neurology
In amyotrophic lateral sclerosis (ALS), early diagnosis is essential for both current and potential treatments. To find a supportive approach for the diagnosis, we constructed an artificial intelligence-based prediction model of ALS using induced plu...