Machine Learning for Diagnosis of a Brain Disorder: An FCFH Project

Turku PET Centre and the Department of Neurology Xuanwu Hospital of Capital Medical University Beijing have teamed up to research the use of machine learning in diagnosing Multiple System Atrophy (MSA). As part of the FCFH network, the Finnish collaborators are responsible for technical analysis, while the Chinese collaborators, led by Dr. Hua Lin, are providing clinical data related to patients.

This research continues a previously published article entitled “Combined functional and structural imaging of brain white matter reveals stage-dependent impairment in multiple system atrophy of cerebellar type,” which appeared in the npj Parkinson’s Disease Journal. Since August 2022, Riku Klén, Jarmo Tehuo, Seyed Hosseini, and Han Chunlei from Turku PET Centre have joined the research team in China to continue the previous work and investigate the feasibility and effectiveness of using machine learning to diagnose MSA.

The aim of this research is to use the predictive power of machine learning to gain insights into the pathological progression of MSA, an adult-onset progressive neurodegenerative disease characterized by Parkinsonism. The results of this work could lead to earlier diagnosis and more effective treatments for MSA.

MSA is a devastating illness affecting millions worldwide, and the need for effective diagnosis and treatment is more pressing than ever. By combining the expertise of researchers in Finland and China and leveraging the power of machine learning, this collaborative effort has the potential to make significant strides in understanding and diagnosing MSA.

This research is still in progress, and it will be exciting to see the results of this collaboration between the Turku PET Centre and the Department of Neurology Xuanwu Hospital of Capital Medical University Beijing.