The Penn Medicine Institute for Biomedical Informatics has launched a free, open-source automated machine learning system for data analysis that is designed for anyone to use, from a high school student looking to gain insight on their baseball team’s statistics, to trained researchers looking for associations between cancer and environmental factors. “Penn AI,” the first widely available tool of its kind, seeks to lower the barrier for entry into artificial intelligence, allowing users to bring in their own datasets or use the several hundred that are available for download within the tool. With a user-friendly dashboard easily run on a laptop, Penn AI is also designed to learn as it goes, ultimately making analysis suggestions based on the “experience” it gains through use.
“The problem with machine learning tools is that machine learning people build them, so they’re usually only usable by those with high levels of training,” says Jason Moore, director of the Institute for Biomedical Informatics and a professor of biostatistics, epidemiology and informatics. “My team has taken three years to develop this system so that it can be approachable by anyone, regardless of their training or experience. Our goal has been to make a free and simple system that is still robust enough to transform the way we approach biomedical research—which I think we’ve accomplished.”
Penn AI is an automated machine learning system, which means that the artificial intelligence engine behind it can work out different analyses with different variables and methods on its own, without needing human input. Machine learning without automation requires someone to choose a specific method and manually adjust each parameter that the AI engine works on, often requiring more advanced knowledge of data in order to get meaningful results. Even for people with that know-how, there is still some guesswork involved. However, automation can eliminate much of that, and as Penn AI is used more and more, it will continually “learn” the best methods for analyzing data and will provide recommendations for its users based on what they are looking to glean.
Read more at Penn Medicine News.