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About
AI-enabled point-of-care ultrasound (AI-POCUS) is emerging as a transformational diagnostic technology, especially for lung diseases, maternal health, emergency care, and primary care in low-resource settings.
AI-enabled point-of-care ultrasound (AI-POCUS) is emerging as a transformational diagnostic technology, especially for lung diseases, maternal health, emergency care, and primary care in low-resource settings.
The CoP aims to:
01
Build literacy and trust
02
Support independent validation
03
Promote safe and ethical use
04
Contribute to global standards development
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Various stakeholders face fragmented knowledge, uneven regulatory readiness, limited training pathways, and uncertain validation standards.
This CoP was created to unite policy-makers, clinicians, developers, implementers, innovators, donors, and researchers to accelerate responsible, effective, and safe adoption of AI-POCUS in LMIC health systems.
Why this & why now?
We address:
01
Lack of shared guidance on AI-POCUS deployment in LMICs
02
Need for consensus on validation, safety, ethics, and data governance
03
Duplication of efforts and fragmented pilots and research projects
04
Limited clinical training resources and capacity
05
Need for context-appropriate procurement and regulatory pathways
Focus Areas
Our focus areas include AI-POCUS for obstetrics, respiratory, TB, emergency, and primary care use cases, AI model validation in LMIC contexts, equitable access to data and models to drive access to health screening in LMIC, training and workforce models for frontline providers, data governance, ethics, and safety, device interoperability and procurement, and iImplementation science for digital health.
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WG 1
AI Validation &
Safety
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WG 2
Clinical Workflows & Training
WG 3
Implementation &
Scale-Up
WG 4
Ethics, Equity & Data Governance
WG 5
Procurement & Tech Suitability for LMICs
These focus areas will translate into the following Working Groups:
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