The patient couldn’t go near a gas station. In fact, the mere smell of gas took him back to Iraq, where he fought in an endless succession of violent skirmishes. One day, an IED exploded right by his Humvee. The blast singed his hair, and the strong oil odor was in his nose, on his clothes, everywhere. The veteran has struggled with PTSD ever since and is one of the 40 million adults in the United States who suffer from some kind of anxiety disorder. Since he’s returned to the States, his car has always run on empty. By the time this patient met Alessandro De Nadai, Ph.D., the last thing he wanted to do was fill it up.
“That’s a completely natural reaction,” says De Nadai, an Assistant Professor of Psychology at Texas State University. “People naturally avoid the situations that make them anxious, but that often makes the anxiety worse.”
How do we automatically turn this info into something doctors can use in helping patients, De Nadai wondered. Better yet, how can we use it to get treatment right the first time?
Since he was a twenty-year-old undergraduate at the University of Georgia, De Nadai has been fascinated by two seemingly unrelated fields: clinical psychology and computer science. Yet as he continued his studies, earning two master’s and a doctorate, De Nadai realized how those two fields can complement one another and help patients get the treatments they need. This veteran was a prime example.
It was 2017, and De Nadai was wrapping up his doctorate in Clinical Psychology with an internship at the VA Medical Center in Jackson, Mississippi. While he watched the veteran detail symptoms, explain family history, and list a litany of other facts about his past and present, De Nadai had an idea.
“How do we automatically turn this info into something doctors can use in helping patients,” De Nadai wondered. “Better yet, how can we use it to get treatment right the first time?”
De Nadai is part of a talented cohort of Texas State professors leading the emerging field of computational medicine. With a slew of data-driven projects, professors of health administration, computer science, psychology and engineering are working together to make the world a healthier place.
“It’s an amazing, cross-disciplinary effort,” De Nadai says. “We have all of these professors coming together to use big data, and that’s pretty exciting.”
One cross-disciplinary project, led by professor Larry Fulton, employs machine learning to analyze MRI scans and predict Alzheimer’s, thereby allowing doctors to intervene and possibly even prevent the illness before it arises. Machine learning is only possible because of data, he says.
“This is the future of healthcare,” Fulton says. “Data is helping us get so much better at diagnostics and helping both doctors and patients. At the end of the day, all of our work is patient-focused and patient-centered.”
Meanwhile, De Nadai is using data to help patients struggling with anxiety, OCD, PTSD, and other afflictions get on the right treatment path as early as possible. A combination of psychology and computer science, computational medicine has emerged as one of the most consequential fields of study.
“It’s really exciting, because there’s no single standard for what we’re doing right now,” he says. “We’re creating the standard that will help thousands and thousands of people.”