This case study report presents the implementation of novel devices of artificial intelligence (AI) and machine learning (ML) into healthcare process, which is one of the themes covered by the project, Artificial Intelligence (AI) Policy Recommendation on Digital Transformation for Healthcare.

Through the detection of diabetes retinopathy for a patient cohort of diabetes mellitus, a demonstration of a model for incorporating AI Box, an AI/ML device, into the provision of healthcare in a resource-limited area. The geographic distribution and limited medical capacity of the area were characterized. The framework for incorporating the AI Box into the workflow of routine healthcare to reach the aim of providing fundus examination at regular basis was demonstrated in a primary care unit. The report concludes that the proposed AI/ML device targeting the unmet need of fundoscopic examination for DM patients in the primary care setting demonstrates the usefulness of AI technologies in improving the accountability of healthcare providers and the accessibility of patients and clients.