Predicting Motor Neuron Disease (MND) Patient Status by Machine Learning

There is an urgent need to identify biomarkers to improve the speed of diagnosis and predict prognosis in motor neuron disease (MND). This project will utilize proteomic technology and machine learning (ML) to identify potential protein biomarkers in cohorts of plasma samples from the MQ Neurodegenerative Diseases Biobank. The identification of proteins and ML can distinguish between clinical parameters, MND subtypes, and evaluate specific proteins biomarkers. The outcome will provide a systematic approach to finding robust MND biomarkers which we anticipate will lead to the development of a clinical diagnostic and prognostic tool for early detection and evaluation of progression.