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As machine learning and deep learning technologies advance thanks to advances in computation, algorithms and data availability, the possibilities of the technology continue to expand in medicine. While these AI-driven approaches have real potential, such systems demand large volumes of representative data, careful privacy and security scrutiny and thoughtful long-term strategic planning. In this Q&A, Kathryn Rough, associate director of the Center for Advanced Evidence Generation at IQVIA, discusses the impact of deep learning on healthcare delivery and recommends steps to take during the design, training, evaluation and deployment phases to increase the likelihood that these models will be safe, effective and ethical when trained on real-world health data. Rough also explores the role of epidemiologists in evaluating these technologies as part of multidisciplinary teams and provides advice for health…