Diabetic retinopathy (DR) is a leading cause of blindness. Artificial intelligence (AI) has been proposed to provide a novel opportunity to increase screening for DR. While it is paramount to ensure AI has adequate technical capabilities to perform accurate screening, it is also important to assess how to best implement such technology into clinical practice. Human-centered design offers a methodology to understand the real-world context and behaviors of individuals, engage stakeholders, and rapidly prototype and test solutions, enhancing usability and avoiding unintended consequences. This review describes the methodology of human-centered design, examining how it has been used within a variety of health care contexts, with a particular focus on how it has been used to implement an AI-based DR screening program. Further research is needed to understand the best strategies to implement and evaluate AI in health care.
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