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.

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.

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.

The MIT Laboratory for Financial Engineering (LFE) and Informa Pharma Intelligence announced a new initiative, Project ALPHA (Analytics for Life-sciences Professionals and Healthcare Advocates).

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

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.

Companies make common data science mistakes. Here’s an expert’s guide to what they are and how to avoid them.

Integrating robots into a manufacturing system is often prohibitively expensive. A new approach could change that.

MIT study explores the key factors behind patient outcomes in clinical trials evaluating new treatments for non-small-cell lung cancer.