Pandemic uncovering AI’s potential for psychiatric epidemiology
Psychiatric epidemiology might be one subspecialty you never knew existed, but it’s come to the fore lately. That’s because the COVID crisis has driven mental-health issues into the medical matrix at the population level.
Interviewing a specialist in the field, Scientific American finds AI has a role to play.
“There’s a ton of advancements happening with machine learning methods trying to identify constellations of risk factors for people who confront a variety of negative outcomes in psychiatry,” says the specialist, Jaimie Gradus, DSc, MPH, of the Boston University School of Public Health.
This could lead to advancements in screening during future pandemics, Gradus suggests.
In some places, such utilization “has already been implemented into screening tools that clinicians use to identify people at high risk for certain outcomes, such as suicide,” she says.
Gradus also notes the pros and cons of telehealth technologies for treating mental-health patients.
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Dave P. has worked in journalism, marketing and public relations for more than 30 years, frequently concentrating on hospitals, healthcare technology and Catholic communications. He has also specialized in fundraising communications, ghostwriting for CEOs of local, national and global charities, nonprofits and foundations.