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The most significant advancement thus far in the field is that of “deep learning,” a subcategory of machine learning that attempts to mimic the way the human brain learns new concepts. A simple definition of deep learning is when a system or algorithm is given a large dataset, and told to look for patterns, without being programmed how to differentiate between the patterns.
Through advances in AI and machine learning, computers are finally able to understand things at a much deeper level than humans ever could. So how can we apply engineering principles for better diagnostics -- even engineer new biological circuits for example -- as bio innovation moves from science to engineering? Andreessen Horowitz general partner Vijay Pande reflects on all this and more |
I of III: applying engineering principles for better diagnostics? |
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What is a medicine, really? From the days of aspirin from willow bark, medicine is as old as humanity itself: something humans have been discovering, designing, and creating for ages to help heal ourselves. But now, thanks to technology, we’re entering an entirely new age where the very definition of what a medicine is, is changing
Faster medical treatment saves lives. Machine Learning is already saving lives, by scouring a multitude of patients’ data and comparing them to one patient’s health data to detect symptoms 12 to 24 hours sooner than a doctor could. "In many pressing medical problems, the answers to knowing whom to treat, when to treat, and what to treat with, might already be in your data" says Suchi Saria. Learn how TREWS (Targeted Real-time Early Warning Score) is leading the way to save lives. Suchi Saria is a professor of computer science and health policy, and director of the Machine Learning and Health Lab at Johns Hopkins University. Her research is focused on designing data solutions for providing individualized care.
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Science
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Technology
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Engineering
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Mathematics
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Empowerment
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