Certain mental health issues can be detected through listening to a patient’s voice, according to Maria Espinola, PsyD, an assistant professor at the University of Cincinnati College of Medicine. She told the Times that depressed patients for instance speak in a flatter, more monotone way and anxiety patients talk quickly, often struggling for breath.
Machine learning algorithms can leverage what experts know about mental health and tone of voice to detect mood and help patients understand and manage their moods.
“A lot can happen in between appointments, and technology can really offer us the potential to improve monitoring and assessment in a more continuous way,” said Kate Bentley, PhD, a clinical psychologist at Massachusetts General Hospital in Boston.
There are a range of apps already on the market for this, including one from Cigna.
At the Becker's 11th Annual IT + Revenue Cycle Conference: The Future of AI & Digital Health, taking place September 14–17 in Chicago, healthcare executives and digital leaders from across the country will come together to explore how AI, interoperability, cybersecurity, and revenue cycle innovation are transforming care delivery, strengthening financial performance, and driving the next era of digital health. Apply for complimentary registration now.
