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In the third blog in our series on artificial intelligence (AI) and machine learning (ML)-driven predictive models (data analytics tool or software) in health care, we discussed some potential risks (sometimes referred to as model harms) related to these emerging technologies and how these risks could lead to adverse impacts or negative outcomes. Given these potential risks, some have questioned whether they can trust the use of these technologies in health care.
We are encouraged to see that some stakeholders are demonstrating that a predictive model is fair,
The post Back to the Future:...
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As you design, market, and distribute a mobile health (mHealth) app that your customers will use to collect, share, use, or maintain individuals’ health information, it is likely you have questions about what U.S. federal laws apply. You may also wonder which federal agencies oversee various aspects of mHealth — including how this varies by how individuals, their health plan, or health care...