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Machine Intelligence in Healthcare: Perspectives on Trustworthiness, Explainability, Usability and Transparency

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Air date: Friday, July 12, 2019, 8:30:00 AM
Time displayed is Eastern Time, Washington DC Local
Views: Total views: 1375, (1018 Live, 357 On-demand)
Category: Conferences
Runtime: 06:40:10
Description: Machine Intelligence (MI) is rapidly becoming key to biomedical discovery, clinical research, medical diagnostics and devices, and precision medicine. In the context of this meeting, MI is defined as the ability of a trained computer system to provide rational, unbiased guidance to humans in such a way that achieves optimal outcomes in a range of environments and circumstances. MI tools can uncover new possibilities for both physicians and patients, allowing them to make more informed decisions and achieve better medical outcomes. When deployed, these outputs can enhance efficiency at every level of the healthcare system.

The challenges are: how do we trust that what the computer tells us is correct when we don’t understand how it arrived at the output/answer? How do we ensure that these outputs are safe and beneficial for human health? And, if we change the data or environment, how does this affect the output? These questions are especially relevant to clinical care decision making – are the risks of using such tools understood and how can the technology be deployed for maximal benefit?
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Author: NCATS, NIH
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CIT Live ID: 33220
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