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DCI Network presents our latest webinar "AI in Healthcare: Real World Data Generation and the Regulatory Perspective"

The pervasive integration of AI into every facet of our lives is an indisputable trend, and its most profound ramifications are notably pronounced within the healthcare domain. This influence came to the forefront at the HIMSS meeting held in April, where practically every prominent company in attendance at the trade show was showcasing their advancements driven by AI technology. This notable upsurge in the adoption of AI holds a range of far-reaching implications for the healthcare industry.

In the wake of this rapid expansion, it becomes imperative to raise and address pertinent questions regarding the data utilized for training AI systems. Considerations extend to the policy and regulatory dimensions of these decisions, along with the strategies regulatory bodies can employ to uphold trust and safety in this new era.

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Cancer is the second-leading cause of death in the United States. In addition, cancer is one of the most frequently diagnosed serious illnesses, with an estimated 16.9 million Americans with a history of an invasive malignancy alive as of January 1, 2019. Nearly 2 million invasive cancer cases were expected to be diagnosed in 2020. At the beginning of the COVID-19 pandemic, Advocate Aurora Health, Dana-Farber Cancer Institute, Fred Hutchinson Cancer Research Center, the University of Miami, and Vanderbilt University Medical Center (VUMC) led the formation of the COVID-19 and Cancer Consortium (CCC19), to rapidly collect and disseminate information about the especially vulnerable population of patients with active cancer and cancer survivors who are diagnosed with COVID-19. CCC19 started accruing data on March 17, 2020. As of September 2022, 123 institutions across North America have joined the consortium, with more than 15,000 cases reported to date. CCC19 maintains a registry to collect granular data about baseline characteristics, initial course of COVID-19, and longer-term outcomes.

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