Overview
Exploring computer vision, Artificial Intelligence (AI), and data science to identify biomarkers to predict disease and stratify patients.
This Digital Health Technology sandpit (Led by Dr Richard Gault, QUB) will explore computer vision, Artificial Intelligence (AI), and data science to identify biomarkers, predict disease, and stratify patients. Learning will be shared through example use cases in ophthalmology and microscopy. The sandpit is targeted at emerging technology, scientific, and healthcare leaders from industry, academic and healthcare trust.
Context
The increasing complexity of laboratory diagnostics, together with the growing demand for cost efficiency and accuracy, has highlighted the potential of computer vision techniques for transforming image-based analysis. This sandpit will explore the extent to which computer vision can support cost reduction and accuracy improvement in diagnostics, while also identifying sticking points in clinical, academic, and industrial practice that must be overcome for successful integration.
Organised by PBIAA
A Belfast academic-led consortium has been awarded a Place Based Impact Accelerator Account (PBIAA) from EPSRC. As part of the funding, a Future Technology Leaders series of “Sandpits” has been organised, bringing together academics, businesses, and clinical and civic partners. This is the second of these sandpits. Each session will address a real-world healthcare challenge, showcase practical technology demonstrations, invite external experts to share insights, and connect local researchers, companies, civic leaders, clinicians, regulators, and policymakers. As part of the place-based focus, the PBIAA seeks to create impact in Belfast and beyond.
