*Reposted* — originally published on 4/21/2021 on byte2bedside.com There is much excitement about AI in healthcare, but we still don’t quite understand how it can produce impact at a meaningful scale. Discussions about AI often jump to examples of machine learning (ML) models that perform eye catching tasks such as interpreting X-rays and diagnosing disease. However, although there is no shortage of published papers describing highly accurate ML models that predict all sorts of clinical outcomes, there is a dearth of actual AI products that are widely adopted and deliver value.
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What can the history of cloud computing teach…
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*Reposted* — originally published on 4/21/2021 on byte2bedside.com There is much excitement about AI in healthcare, but we still don’t quite understand how it can produce impact at a meaningful scale. Discussions about AI often jump to examples of machine learning (ML) models that perform eye catching tasks such as interpreting X-rays and diagnosing disease. However, although there is no shortage of published papers describing highly accurate ML models that predict all sorts of clinical outcomes, there is a dearth of actual AI products that are widely adopted and deliver value.