Anxiety and depression are surprisingly common among young children – as many as one in five kids suffer from one of them, starting as early as the preschool years. But it can be hard to detect these conditions, known as “internalizing disorders,” because the symptoms are so inward-facing that parents, teachers and doctors often fail to notice them.
So McGinnis teamed up with Ellen McGinnis, a clinical psychologist at the University of Vermont, and colleagues in the Department of Psychiatry at the University of Michigan, Maria Muzik, Katherine Rosenblum and Kate Fitzgerald, to develop a tool that could help screen children for internalizing disorders to catch them early enough to be treated.
La inteligencia artificial ya es capaz de detectar depresión en niños: Investigadores estadounidenses han desarrollado un algoritmo de aprendizaje automático, basado en inteligencia artificial, que es capaz de detectar signos de ansiedad y depresión en los patrones del habla de los niños pequeños.
Ellen McGinnis and Ryan McGinnis of the University of Vermont, lead researchers on a study published in PLOS ONE that showed wearable sensors could detect hidden anxiety and depression in young children. (Photo: Josh Brown)
