BRaIn Disease monitoring throuGh the lifE span powered by Artificial Intelligence

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Identifiant

Unité de recherche

SEFRI

Numéro de projet

25.00218

Titre du projet

BRaIn Disease monitoring throuGh the lifE span powered by Artificial Intelligence

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	Allemand	Français	Italien	Anglais
Résumé des résultats (Abstract)	-	-	-

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Résumé des résultats (Abstract) (Anglais)	BRIDGE-AI will train a new generation of innovative and entrepreneurial-oriented doctoral candidates (DCs) to move the state-of-the-art away from the snapshot interpretation of medical images by AI to a longitudinal follow-up and prediction of disease progression, covering a wide range of brain disorders across the entire lifespan. In an innovative departure of prevalent training models, each of BRIDGE-AI's DCs will be co-supervised by internationally leading experts from university research in biomedical image computing, world-renowned research hospitals, leading scanner manufacturers (Siemens, Philips) and medical imaging AI companies (incl. Bayer). Through this unique network, BRIDGE-AI will complete the entire circle from clinical needs to image acquisition, academic AI solution proposal, and commercial product for tracking disease progression and predicting treatment response in individual patients. Each of BRIDGE-AI's DCs will have a dedicated multidisciplinary and multisectoral thesis board, receiving input from industry, academia, and hospitals, and having access to large collections of clinical neuroimaging data, facilitating the evaluation of the true clinical relevance and impact of the proposed disease monitoring tools. Wide dissemination of the obtained methodological advances will be ensured by adopting a strong network-wide focus on open-source software.

Catégorie

Texte

Résumé des résultats (Abstract)
(Anglais)

BRIDGE-AI will train a new generation of innovative and entrepreneurial-oriented doctoral candidates (DCs) to move the state-of-the-art away from the snapshot interpretation of medical images by AI to a longitudinal follow-up and prediction of disease progression, covering a wide range of brain disorders across the entire lifespan. In an innovative departure of prevalent training models, each of BRIDGE-AI's DCs will be co-supervised by internationally leading experts from university research in biomedical image computing, world-renowned research hospitals, leading scanner manufacturers (Siemens, Philips) and medical imaging AI companies (incl. Bayer). Through this unique network, BRIDGE-AI will complete the entire circle from clinical needs to image acquisition, academic AI solution proposal, and commercial product for tracking disease progression and predicting treatment response in individual patients. Each of BRIDGE-AI's DCs will have a dedicated multidisciplinary and multisectoral thesis board, receiving input from industry, academia, and hospitals, and having access to large collections of clinical neuroimaging data, facilitating the evaluation of the true clinical relevance and impact of the proposed disease monitoring tools. Wide dissemination of the obtained methodological advances will be ensured by adopting a strong network-wide focus on open-source software.