How is AI changing health care? An Expert Viewpoint from CI MED Dean Mark Cohen

Artificial intelligence tools have opened new pathways for physicians and researchers to deliver patient care and further medical discovery. Dr. Mark Cohen, dean of the Carle Illinois College of Medicine at the University of Illinois Urbana-Champaign, talked with News Bureau biomedical sciences editor Liz Ahlberg Touchstone about the risks and rewards of using AI tools in health care and medical discovery.

Learn more in the video or by copy and pasting the link here: https://news.illinois.edu/view/6367/1124587113

Sample of Content:

How can AI help physicians care for patients?

There are several ways that AI can benefit physicians in terms of patient care. AI as a tool can provide a lot of information to a physician in real time, which saves them from having to look up a variety of different sources, so it can be a time saver in the clinic. It also can organize information in a way that’s much more presentable and easier to digest, so there are a lot of areas around documentation in the clinic where AI tools could be very helpful. For example, if you had an AI tool that was listening to a conversation between a provider and a patient, it could summarize that conversation into a medical note that could then be put into the record after review.

How could AI help with medical discovery, like drug or device development?

It’s really exciting to think about how data can be used more effectively. We already have data from your electronic medical record, data from different tests and results that you've had over the years, data from genetics. What if AI tools could take all those data sets and make a digital version of you that it can then evaluate? When a new drug is considered, it can ask, is that the right drug for your particular condition, and based on your genetics, your history, is it going to work well? It can run thousands of probabilities and risks all in seconds to say this drug might be a good fit, or suggest what the next best option could be. Another area where AI can be useful is drug discovery. AI can analyze millions of different types of chemical formulas and create new molecules with medicinal properties. Similarly with devices, thousands of variants can be prototyped virtually to optimize parameters and think about how to apply new devices in patients. AI tools can really help accelerate some of that evaluation process, as well as defining potential new options or pathways for discovery.

This past year, we at CI Med created a new global consortium of innovation and engineering in medicine that brings together medical schools, engineering schools, companies, government agencies and regulatory agencies to think about how as a large, diverse, interdisciplinary group, we can solve some big data problems together. One of those is creating a global de-identified data warehouse that could be an amazing tool. What if AI solutions could look at not just a thousand patients or a million patients, but 500 million patients around the world and solve some real problems around rare diseases, cancer, or some chronic diseases that we are only scratching the surface of with limited data? With new tools like quantum and other ways to make sure that data is safe and encrypted, such an endeavor could take us to the next level of how we think about healthcare solutions and how we think about collaborations across the world.

How is CI Med using AI to train future physician-innovators?

We have an imperative as a medical school to think about the next generation, and technology is only going to become more and more immersed in how we think about our future in medicine. If we’re not training that next generation to use those technologies more effectively, then we are doing a disservice to the future. CI Med is the world’s first engineering-based medical school. We were founded on the principle that this intersection of technology and engineering is an important part of how to teach medical students how to become future physician-innovators who can lead interdisciplinary teams to think about how to solve bigger problems in health care. Our focus has been really proactive to think about better educating medical students to use tools like AI in all of these different domains.