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Artificial intelligence is becoming a bigger part of MU research.
The use of machines to mimic human intelligence and collect data is now a prominent feature in cancer research, the study of muscle movements, treatment of neurological disorders and other disciplines at the university.
At MU’s Ellis Fischel Cancer Center, a new artificial intelligence — or AI — software known as Ethos is being used to provide a more accurate and concise radiotherapy to treat patients.
Ethos was developed by Varian, a medical technology company based in California. The technology makes it easier for caregivers to track the area each cancer treatment dose goes to, and modify patient care as needed.
“We want to come up with the best possible treatments for our patients in the community,” Gregory Biedermann, MU assistant professor of radiation oncology, said in an interview Wednesday.
MU began using Ethos Nov. 9, he said. Six patients are now being treated using the technology.
“It’s been a slower process of making sure we’re getting familiar with it and identifying this is not for every patient as well,” Biedermann said.
Ethos is a new radiation therapy machine, but it’s not the sole treatment MU will use from now on. Ellis still has another radiotherapy machine they will use, as well as other various forms of treatment depending on the patient. Ethos provides patients and doctors with another treatment option based on the advantages it will give the patient.
While it’s too early to determine Ethos’ success on MU cancer patients, Biedermann said he’s noticed small victories and ultimate success will be measured in the weeks to come.
“This is measured after they’re done and their follow ups weeks and months later. We’ll see what type of response they have and how they will recover from everything we’re doing,” Biedermann said.
Traditionally, dissection was required for researchers to study muscle and anatomy, which can be disruptive and irreparable.
Artificial intelligence is changing that for MU professors such as Kevin Middleton, Casey Holliday and Carol Ward.
Middleton, who works in the MU Division of Biological Sciences, is now adapting it to his study of the function and evolution of dinosaurs. Using 3D and CT imaging on the head of a Tyrannosaurus rex, for example, Middleton can study how its muscles worked and evolved.
That research can be interpreted to understand the way animal bodies work and transfer that knowledge to humans.
CT scans have come a long way in the research community, said Middleton. CT scans used in hospitals were not sufficient for his research, but software improvements are now allowing researchers to scan rocks and fossils, taking research to an entirely new level.
“The ability to do this sort of work has really expanded,” he said. “We actually can handle datasets that are in the 100 gigabytes or more, which is just an unreal amount of data.”
Holliday, an associate professor of anatomy at the MU School of Medicine, said studying animal muscles allows them to apply their findings to people with Parkinson’s disease or other musculoskeletal disorders.
“(We) use it to show how muscle architecture might change with different aspects of disease or injury,” Holliday said. “It lets us kind of see inside of things in a way that we never did before.”
Ward uses the technology to study ape and human evolution.
Working together with Holliday and Middleton, she is looking into the complex anatomical system of the hand, its bones, joints, muscle and soft tissue and how they grasp and move, as well as the way the hand evolved.
Ward’s ultimate goal is to understand the evolution of locomotion in monkeys, apes and humans.
“There’s lots of intellectual parts, intellectual components,” Ward said. “There certainly might be sort of down the road ways that some of these methods could be applied to clinical data. And that could be used for patients.”
The team hopes to understand this to figure out what bones might tell us about biomechanics and study this evolution, she said.
Artificial intelligence does have its limitations because it’s only as good as the data it’s trained on.
“We’re basically trying to remake what reality truly is inside of our anatomy,” Holliday said. “But we don’t want to get too married to the models, the data, like the fabricated idea of what reality is. We always try to backtrack and validate everything that we do, compared to what the computer tells us.”
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