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AI holds tremendous promise for both the administrative and clinical sides of healthcare, but obstacles still remain. One of the major hurdles is tied to patient privacy and the sharing of vast amounts of data needed to effectively tune AI models.
Even if patient data is de-identified, healthcare organizations often are still reluctant to share data for machine learning and Al efforts, said Peter McGarvey, director of the innovation center for biomedical informatics at Georgetown University, who moderated a panel discussion at an AI forum hosted by the institution and the World Bank on Tuesday.
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