Improving Early Diagnosis of Amyotrophic Lateral Sclerosis: A Multimodal Literature Review

Abstract

Amyotrophic lateral sclerosis (ALS) is a rare, progressive neurodegenerative disorder characterized by the degeneration of upper and lower motor neurons. Due to the clinical heterogeneity of the disease, early diagnosis remains a critical challenge. This study presents a systematic literature review aimed at identifying diagnostic methods that facilitate early ALS detection. Relevant peer-reviewed studies published between 2020 and 2026 were analyzed using a thematic approach, focusing on clinical evaluation, neuroimaging, electrophysiological techniques, biomarker-based methods, and emerging artificial intelligence applications. Findings indicate that while electromyography and neuroimaging are currently the most widely used diagnostic methods, the integration of biomarker research and AI-assisted decision-making holds promise for improving early detection. The review highlights existing gaps in diagnostic sensitivity and accessibility, emphasizing the need for multimodal approaches to reduce diagnostic delays. These insights aim to guide clinicians, researchers, and healthcare professionals in implementing strategies that improve early identification of ALS and patient outcomes.