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Equipe Langage, Research
![Projet BIOMOD](/sites/default/files/Mediatheque/Recherche/Projets%20en%20cours/biomod_bouton.jpg)
The contribution of artificial intelligence methods to the diagnosis of neurodegenerative diseases based on multimodal biomarkers
Monica BACIU
Mathilde SAUVEE
Olivier MOREAUD
The incidence of cognitive neurodegenerative diseases (CND) increases with age. Alzheimer's disease (AD) is the most common. Other diseases related to Alzheimer's disease (AD) share common features with AD, but vary in terms of genetics, clinical course, neuropsychology, proteinopathy, neuroimaging, evolution and management. A major advance is the use of biomarkers in CSF to approach neuropathological diagnosis. Artificial intelligence (AI) methods applied to multimodal parameters have real phenotyping potential (i.e. automatically identifying multimodal characteristics specific to a pathology, enabling it to be distinguished from others). In addition, the development of AI-based clinical decision support atlases is booming. We have a retrospective database with prospective potential that will enable us to carry out this project.
An example is provided in the image above.
CN= cognitive normal; sMCI= Stable mild cognitive impairment; pMCI= Progressive MCI; AD= Alzheimer's disease; FTLD: Frontotemporal Lobar Degeneration.
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