Digital health solutions provider Audere has secured a fresh grant worth $9.35m from the Bill and Melinda Gates Foundation to continue the development of its HealthPulse AI technology.
The artificial intelligence (AI)-powered HealthPulse AI is designed to enhance the accuracy of the rapid diagnostic test (RDT) use and digitise RDT data for programme reporting.
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Bill and Melinda Gates Foundation Malaria PST director Philip Welkhoff said: “We are excited to continue our support of HealthPulse AI and believe this will make an impact on malaria disease surveillance and quality-case management as we progress toward eradication.”
The new funding comes after the Bill & Melinda Gates Foundation provided funding worth $17.25m in 2018.
The company also received support from other global health partners including PATH, Aurum Institute and FIND.
Audere CEO Dino Rech said: “This new grant positions us to cost-effectively scale the technology – essentially turning any camera into a quality RDT surveillance tool, thereby maximising impact.”
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By GlobalDataHealthPulse AI can be deployed to support several use cases such as real-time community-based pandemic preparedness and surveillance at scale, private-sector health delivery and virtual care models for diagnostic testing and treatment.
It is provided through a mobile app or an integration toolkit, delivered as a set of web services or a mobile software development kit.
The platform’s features can be used as a set of standalone tools or as an end-to-end integrated solution, including guided administration, AI-verified image capture, connection to care, result-decision support and patient-level data and insights.
Furthermore, HealthPulse AI works on commodity smartphones, which are common in low and middle-income countries, without the need for new hardware or paper cards. It is designed to be RDT-brand agnostic to support any RDT.
The platform uses accurate AI models that leverage advanced machine learning and computer vision to improve the interpretation of RDT rest.
It provides an accuracy rate of 90% to 95% in adversarial, real-world conditions.
