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Artificial Intelligence in Medicine: Lessons from COVID-19 (Preprint)
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1
Autoren
2020
Jahr
Abstract
<sec> <title>UNSTRUCTURED</title> The dramatic effects of the novel coronavirus have been felt deeply worldwide. As of the time of writing, almost 600,000 lives have been lost, unemployment claims have reached record heights, and entire sectors of various economies have been largely shut down. Yet from tragedies of such grand scale, important lessons can be learned: about the economic structure of healthcare, about future systems of employment and government aid, and about the use of emerging technologies in medicine and healthcare. In this article, I focus upon the use of artificial intelligence in medicine, and identify two lessons that can be learned from the COVID-19 global health crisis. I argue that high-stakes scenarios like those emerging from COVID-19 pose an especially challenging tension between patient confidentiality and the efficacy of AI in medicine, and that confident predictions of cost-savings and greater efficiency ought to be eyed with suspicion. </sec>
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