Health IT Analytics April 13, 2021
The system brings hospital data through a set of machine learning models to help inform clinical decision-making.
Researchers at MIT’s Data to AI Lab (DAI Lab) have developed a new framework that can streamline machine learning processes to help organizations uncover actionable insights from big data.
The system, called Cardea, is open-source and uses generalizable techniques so that hospitals can share machine learning solutions with each other, leading to increased transparency and collaboration.
To develop Cardea, researchers leveraged automated machine learning, or AutoML. The goal of AutoML is to democratize predictive tools, making it easier for people to build, use, and understand machine learning models.
AutoML systems like Cardea surface existing machine learning tools instead of requiring individuals to design...
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