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00:10 — Acceleration Economy Analyst, Paul Swider covers three topics involving global health and AI:
- How machine learning is saving lives today in healthcare
- How machine learning is making an impact in global health
- How to use a global perspective to transform healthcare in the U.S.
00:46 — The first two computer science problems solved with machine learning were object recognition with speech and vision.
01:10 — There has been a huge explosion of how NLP and speech are being used with robotics, especially during the pandemic. Following the pandemic, there has been an increase in using bots to translate natural languages. Further, we’re triaging patients based on symptoms which allow for streamlining care and saving lives.
01:46 — Object recognition is being used with healthcare to screen for things, such as different types of cancer.
02:32 — The NHS in the United Kingdom recently implemented smart beds, which are hospital beds connected just like any other edge device. The smart beds drop data points for AI to process. The data is used for machine learning and training, triaging and moving patients around, and maintaining an accurate bed count across the NHS.
03:22 — This system works in the United Kingdom because they have a centralized healthcare system, which means they have a centralized data set. This universal structure set of data is something that is also being worked on in the U.S. as a collaboration between healthcare and machine learning.
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