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Automating ML and AI to improve speed, accuracy of predictive models
AI/ML

Automating ML and AI to improve speed, accuracy of predictive models

3:58

(Sponsored) DataRobot describes how advances in auto-machine learning and predictive analytics are enabling healthcare enterprises to be AI-driven.

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7:13

Lack of regulation may stifle AI innovation

Peiling Yap, chief scientist at HealthAI, says that many responsible AI projects never move beyond pilot stages because weak governance and a lack of clear regulatory guardrails block safe scaling and widespread adoption.

Lack of regulation may stifle AI innovation
Peiling Yap, chief scientist at HealthAI, says that many responsible AI projects never move beyond pilot stages because weak governance and a lack of clear regulatory guardrails block safe scaling and widespread adoption.
7:13
8:24

AI may mimic intelligence but remains artificial

Mikhail Golovnya, senior advisory data scientist at Minitab, says that modern AI, although it is now more accessible to non-scientists, is still just a form of machine learning and is not as powerful as some believe.

AI may mimic intelligence but remains artificial
Mikhail Golovnya, senior advisory data scientist at Minitab, says that modern AI, although it is now more accessible to non-scientists, is still just a form of machine learning and is not as powerful as some believe.
8:24
3:51

Reduce AI liabilities with healthy skepticism

The biggest risks of healthcare artificial intelligence are not necessarily the known deficiencies of AI technology. "The real risk is automation complacency," says Ben Scharfe, EVP of AI at Altera Digital Health.

Reduce AI liabilities with healthy skepticism
The biggest risks of healthcare artificial intelligence are not necessarily the known deficiencies of AI technology. "The real risk is automation complacency," says Ben Scharfe, EVP of AI at Altera Digital Health.
3:51