SOURCE-LINKED INTELLIGENCE

IMAGING FOR PATIENT BENEFIT IN ARTHRITIS

CORDIS · observation · Publication date unknown

imaging technologies for the benefit of patients by creating new powerful analysis and decision tools. We will first generate tools to transform unstructured images into quantitative biomarkers using artificial intelligence (AI) and machine learning (ML) models, and validate them clinically for their diagnosis, monitoring and prognosis power. This will considerably increase the utility of imaging biomarkers for arthritis and bring them to the same level as laboratory biomarkers. In parallel we will develop accessible imaging strategies such as remote monitoring and robotic-powered point-of-care ultrasound exams for patients to mitigate the often-observed shortage of qualified personnel in real world settings. To achieve this, we will improve the precision and interpretability of these methods and further validate them with clinical, molecular and histological analyses. Our consortium is built on multi-disciplinarity and the constant synergistic interaction of all the actors of arthritis care: rheumatologists, radiologists, patients, researchers, regulators, industries and small- and

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recordType

award

status

SIGNED

region

EU

value

10729428.06

unit

EUR