Researchers launched an in-house Data Science and Artificial Intelligence (DSAI) challenge to beat MIT’s machine-learning models for predicting clinical trial outcomes. The results are now available.
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Integrating robots into a manufacturing system is often prohibitively expensive. A new approach could change that.
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AI is a tool to get things done. To use it properly and generate value, organizations need the right capabilities — including a good understanding of data.
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In a new book, MIT roboticist Daniela Rus looks at the powers and limitations of robots and how humans can work with them to unlock new capabilities.
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Companies make common data science mistakes. Here’s an expert’s guide to what they are and how to avoid them.
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MIT Sloan and CSAIL researchers apply artificial intelligence techniques to one of the largest datasets of clinical trial outcomes to handicap the drug and device approval process
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Machine learning is a powerful form of artificial intelligence that is affecting every industry. Here’s what you need to know about its potential and limitations and how it’s being used.
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This page contains recent media, interviews, and conference appearances by FSAS affiliated faculty and researchers
The Food Supply Chain Analytics and Sensing (FSAS) Initiative is creating predictive analytical tools and technologies to improve the design and management of safe and reliable food supply chains
