University of Birmingham > Talks@bham > Facts and Snacks > FnS - Combining magnetic resonance spectroscopy with machine learning to establish individual differences in brain metabolism

FnS - Combining magnetic resonance spectroscopy with machine learning to establish individual differences in brain metabolism

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If you have a question about this talk, please contact Mirco Giacobbe.

Magnetic resonance spectroscopy (MRS) is a non-invasive technique for measuring metabolite signals from within the human brain. Common clinical applications include brain tumour diagnosis and neurometabolic disorders, where large changes in spectral profiles are typically seen. However, dynamic changes in brain tissue metabolism and differences between individuals are poorly understood due to the technical challenges of detecting these small differences. Through advances in the acquisition and analysis of MRS data, we have shown how state-of-the-art techniques can detect robust differences in healthy brain metabolism between individuals that remain stable over a period of months. More recent work includes the application of machine learning techniques, such as partial least squares-discriminant analysis, to discover spectral features with the potential to act as novel biomarkers of brain health.

The talk will also be streamed on zoom: https://bham-ac-uk.zoom.us/j/85289214035

This talk is part of the Facts and Snacks series.

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