Artificial Intelligence for Motor Neuron Diseases: A Comprehensive Review of Detection, Diagnosis, and Prognosis

Abstract

Motor Neuron Diseases (MNDs), particularly Amyotrophic Lateral Sclerosis (ALS), are progressive neurodegenerative disorders characterized by the degeneration of motor neurons, resulting in progressive muscle weakness and loss of motor function. Early and accurate diagnosis remains a major challenge due to heterogeneous clinical presentations, overlapping symptoms with other neurological disorders, and the limited sensitivity of conventional diagnostic approaches during the early stages of disease. Artificial Intelligence (AI), including Machine Learning (ML) and Deep Learning (DL), has emerged as a promising approach for identifying subtle disease-related patterns from diverse clinical and biomedical data. This review examines and analyses existing AI-based approaches for the early detection and diagnosis of MNDs using different data modalities, including electromyography (EMG), magnetic resonance imaging (MRI), neuro-physiological signals, speech and voice characteristics, wearable sensor data, genetic information, and other digital biomarkers. The reviewed studies are compared based on the AI techniques employed, data modalities, diagnostic performance, advantages, and limitations. Particular attention is given to multimodal AI, explainable AI, and emerging approaches for patient-specific diagnosis and disease prediction. The review also identifies major challenges, including limited datasets, data heterogeneity, and lack of external validation, interpretability, and difficulties in translating research models into clinical practice. Finally, potential future directions are discussed for developing robust, interpretable, and clinically applicable AI frameworks for earlier and more precise detection of Motor Neuron Diseases.

KEYWORDS: Motor Neuron Diseases; Amyotrophic Lateral Sclerosis; Artificial Intelligence; Machine Learning; Deep Learning; Early Diagnosis; Digital Biomarkers; Multimodal AI.