In association with KQCodes, ARC proudly presents the TechSocial Series. In January, we will be joined by David Guzman, Research Fellow in Machine Learning for Early Disease Diagnosis, London Centre for Nanotechnology, UCL, to talk about Mobile phones, rapid tests, and AI; to Antimicrobial Resistance and beyond..
A series of FREE, informal TALKS, DISCUSSION and PIZZA! Open to anyone interested in computational research methods, technology and innovation, this series covers a broad range of tools, programs, digital environments & language.
Join us every month at 90 High Holborn
Abstract
How can a smartphone function as a medical device? In this talk, we explore how AI and mobile technologies can support health diagnostics and disease surveillance, expanding access to care; especially in low-resource settings such as community healthcare and low- and middle-income countries.
Our team, part of the Digital Health Hub for AMR (digitalamr.org), has been tasked with developing a prototype for AI-enabled diagnostics on mobile devices. The solution is built around three core functions: capture images of rapid diagnostic tests (RDTs) used in point-of-care testing, classify them on-device, even when offline, and connect these results with electronic patient records securely.
We discuss how combining RDTs with AI models deployed on smartphones can improve the accuracy and consistency of test interpretation while making clinical and public health monitoring more widely accessible. We also show how the use of Open Neural Network Exchange (ONNX) technologies allows us to run on-device multiple AI-models efficiently, while giving data scientists and AI researchers freedom to work in their preferred frameworks. We address the challenges around secure integration with electronic patient records, and our architecture using SMART (Substitutable Medical Applications and Reusable Technologies) and FHIR (Fast Healthcare Interoperability Resources) technologies. We also reflect on the implications around usability and clinician engagement, and the role of human-computer interaction and UX design methodologies in shaping the development process of AI-driven mobile apps for health.
Attendees will have the opportunity to test the prototype at the event.
About the speaker
David is a Research Fellow in Machine Learning for Early Disease Diagnosis. His current work focuses on the development of research software for AI-driven health applications, mobile app development, and secure integration of data with electronic patient records. He has over 15 years of experience in the end-to-end design and implementation of software and data platforms for health research, primarily with Java-based technologies, databases, AI, mobile, and web.
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90 High Holborn
WC1V 6LJ
London
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