National AI Campus Helps Advance Medical, Scientific Innovation

Newswise — LOS ANGELES (March 14, 2024) -- One group is using machine learning to develop a more reliable and efficient screening method for bladder cancer.  

Another is studying how artificial intelligence (AI) technology can help predict disease outcomes through X-rays, CT scans and MRI images.

A third group hopes to predict COVID-19 outbreaks using genomic data that machine learning algorithms understand.

This is a sampling of the eight projects that more than 170 undergraduate and graduate students, postdoctoral students, scientists, medical residents, faculty members and others working in scientific or medical institutions are participating in this spring through Cedars-Sinai’s National AI Campus. This project-based learning initiative is in its second year at Cedars-Sinai, and it brings together AI experts and people from various educational and professional levels to address challenging problems in science and medicine using AI and machine learning.

National AI Campus is part of the Center for Artificial Intelligence Research and Education, a component of the medical center’s Department of Computational Biomedicine. It was developed in 2018 by Xiuzhen Huang, PhD, research professor in Computational Biomedicine, when she was at Arkansas State University. When Huang joined Cedars-Sinai, she brought National AI Campus along. Today, National AI Campus is connected to a nationwide program with participants from diverse academic programs and institutions and also includes high school students.

“National AI Campus makes artificial intelligence accessible to a broad community by offering a collaborative, highly interactive training program in which everyone can learn from each other,” Huang said. “At Cedars-Sinai, because of our focus as a medical center and academic institution, we tailor our program around biomedically related projects. We offer medical imaging and genomic projects, as well as those focusing on business analytics and social sciences.”

National AI Campus is free of charge and open to anyone working at Cedars-Sinai or at other invited institutions—at any experience level, in any degree or area of specialty, and with or without previous programming, machine learning or high-performance computing experience.

“All you need is a willingness to learn the basics and an interest in exploring the leading edge of AI and machine learning in medicine,” said Professor Jason Moore, PhD, chair of the Department of Computational Biomedicine, director of the Center for Artificial Intelligence Research and Education and chair of the National AI Campus Steering Committee.

“Artificial intelligence has great potential to improve modern life by addressing many of society’s major challenges, particularly those related to human health. At Cedars-Sinai, our ultimate goal is to one day move our findings into the clinic to help patients.”  

AI makes it possible for computers to perform tasks that require human intelligence. Machine learning is a subset of artificial intelligence in the computer science field. It gives computers the ability to “learn” with data, without being explicitly programmed, and it recognizes patterns in large amounts and diverse types of data to generate important insights.

There are two phases of the National Campus AI program, and each phase lasts four months. To ensure each phase is successful, Huang enlisted Ryan Urbanowicz, PhD, a research assistant professor in the Department of Computational Biomedicine, to serve as director of the campus program, and Joshua Levy, PhD, director of Digital Pathology Research, as associate director.

During Phase One, small interdisciplinary teams of up to 20 people work individually and as a group—online and on their own time—on a project. The teams are led and mentored by experts who have experience in each project topic. Phase One culminates with a showcase of team presentations, including to the Cedars-Sinai research community. This year’s showcase is planned for the summer.

During an optional Phase Two of the program, participants are selected to be part of a global AI competition or a novel Cedars-Sinai-based collaborative research project aiming toward publication in a peer-reviewed medical journal. Cedars-Sinai’s National AI Campus teams won Phase Two competitions in 2023 and have been recognized nationally and internationally.

More than 50 universities across the U.S. also participate in National AI Campus, including 21 historically Black colleges and universities. Cedars-Sinai experts are working to expand the program to California universities and are helping California State University at Dominguez Hills start its own National AI Campus program.

One participant in Cedars-Sinai’s spring 2024 National AI Campus program kickoff said she works in research administration. She noted that she was eager to learn ways to use AI to make data analysis more precise and efficient in her job and to learn skills she could use in other ways.

This feedback aligns with another goal of National AI Campus, Huang said: to create a strong educational resource for students and faculty members and enhance workforce development in AI.

“AI technology is impacting our lives in a major way,” Huang said. “I compare it to when the steam engine came along 300 years ago, bringing dramatic change and transforming industry. AI is another powerful invention that is making significant changes, and although there is some societal anxiety around how to safely use it, I always emphasize that AI will change our life, but it will never replace our life.

“It’s important that Cedars-Sinai harnesses the potential that AI and machine learning offer, and one way we are doing that is through National AI Campus.”

Read more on the Cedars-Sinai Blog: Physician Shadowing Program Offers Students Rare Access