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Computer assisted diagnosis with lung ultrasound for community based pulmonary tuberculosis triage in Benin, Mali and South-Africa

CORDIS · observation · Publication date unknown

t patients presenting at the primary healthcare level. This initiative focuses on generating population-tailored evidence and advocating for the integration of computer-assisted diagnosis (CAD) using artificial intelligence (AI) to support the implementation of lung ultrasound (LUS) into healthcare policy. Unlike typical vertical triage tests, US has multiple other existing AI-assisted diagnostic tools and can facilitate a multi disease approach after TB exclusion, including for pneumonia and cardiovascular assessment. We propose to externally validate and deploy a novel digital technology adapting image-based analysis tools and software for mobile phone ultrasound applications. AI technology sharing serves as one of its key pillars. The adoption of CAD-LUS requires a comprehensive, interdisciplinary, translational approach to clinical research. Our consortium comprises these key fields, including clinical research, diagnostics, implementation science, social science, health economics and policy translation, as well as data/computer science. It addresses all expected outcomes and con

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recordType

award

status

SIGNED

region

EU

value

6809786.25

unit

EUR