Arnav Atluri

Development of a Machine Learning Model for Early Detection of Amyotrophic Lateral Sclerosis (ALS) Using Speech and Stability Analysis

Started June 14, 2024

Abstract or project description

Amyotrophic Lateral Sclerosis (ALS) is a progressive neurodegenerative disease that often goes undiagnosed for months after symptom onset. To address this challenge, I developed a mobile app powered by machine learning that analyzes both speech patterns and physical stability to assist in the early detection of ALS. The app evaluates user voice recordings and balance data, comparing them to a dataset of healthy individuals and ALS patients to detect early signs of motor neuron degradation.

Through multiple model iterations, including Random Forest and Gradient Boosting algorithms, the system achieved strong diagnostic accuracy and demonstrated potential as an accessible, at-home screening tool for ALS. This research highlights how artificial intelligence and data science can be used for social good—improving healthcare accessibility and early intervention for patients in underserved areas.