AI in Healthcare: From Data, Insights, Policies, to Impact (Intermediate; Added Fee)

This workshop offers an in-depth exploration of how artificial intelligence (AI) is transforming the healthcare sector, specifically through real-world data (RWD) and real-world evidence (RWE), thus extending its positive impact into other critical areas of our lives. This workshop aims to bridge the gap between cutting-edge AI technologies and their practical applications in research and clinical practice, showcasing the immense potential of AI to drive meaningful change in healthcare and beyond into areas such as education and social justice.Following the 21st Century Cures Act in the United States (US), RWE has been well-defined. According to the US Food and Drug Administration, RWD means “data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources”. RWE is “clinical evidence about the usage and potential benefits or risks of a medical product derived from analysis of RWD”. RWD can be from a variety of sources, such as “electronic health records, medical claims data, data from product or disease registries, and data gathered from other sources (such as digital health technologies) that can inform on health status.”With the great emphasis on RWD and RWE also comes a variety of challenges and novel ways to optimize and enhance patient-centricity in the development of new therapeutics, whether by informing target selection, designing randomized controlled trials (RCTs), or enabling personalized medicine.Such a big data ecosystem includes novel ways to evaluate disease burden and patient heterogeneity, increased ability to access, generate and leverage fit-for-purpose data sources, and opportunities to harness cloud computing for enhanced scalability and interactivity of digital tools. This includes novel means of gathering data, such as decentralized RCTs to facilitate broader patient access, electronic patient-reported outcomes (PROs) capture, digital wearables, and bring-your-own-device (BYOD) designs. With this increase in volume and variety of patient-centric data also come increasing opportunities to adopt and deploy artificial intelligence (AI), machine learning (ML), deep learning (DL), digital health, robotics, and medical devices to unlock novel and timely insights. This workshop serves the purpose of showcasing and exemplifying the latest advancements in RWE, digital innovation, and AI to enable and improve health care.