Crowdsourcing to better forecast drug approvals
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.
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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The project is charting a course toward more rigorous, coherent methods for ESG integration, with four key goals that are relevant to asset owners and managers, as well as regulators.
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Integrating robots into a manufacturing system is often prohibitively expensive. A new approach could change that.
Our mission is to provide the best education to students to tackle ongoing sustainability challenges.
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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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Online interface simulates 100 years of energy, land and climate data in less than one second to identify solutions to limit warming to within 2 degrees Celsius by 2100
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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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National Capital Protocol Toolkit (NCT) offers companies a structured process to identify key business risks and opportunities in their management of natural resources.