Reading Our Minds: New book issues strong call to action to modernize psychiatry

The Rise of Big Data Psychiatry (The Wall Street Journal): As a physician, I need to figure out three things when a new patient walks into my office: what their life is typically like, what has changed that made them seek treatment and what I can do to help them. It’s a complex problem, and most fields of medicine approach it by taking measurements. If I were a cardiologist evaluating a patient’s chest pain, for instance, I would speak with the patient, but then I would listen to their heart and measure their pulse and blood pressure. I might order an electrocardiogram or a cardiac stress test, tools that weren’t available a century ago. Because I’m a psychiatrist, however, I evaluate patients in precisely the same way that my predecessors did in 1920: I ask them to tell me what’s wrong, and while they’re talking I carefully observe their speech and behavior. But psychiatry has remained largely immune to measurement. At no point in the examination do I gather numerical data about the patient’s life or behavior, even though tools for taking such measurements already exist. In fact, you likely are carrying one around in your pocket right now. Keep reading essay HERE, adapted from the new book Reading Our Minds: The Rise of Big Data Psychiatry by psychiatrist Daniel Barron. Relevant Study: A machine learning approach predicts future risk to suicidal ideation from social media data (NPJ Digital Medicine). From the Abstract: Machine learning analysis of social media...
Source: SharpBrains - Category: Neuroscience Authors: Tags: Brain/ Mental Health Technology & Innovation big data Big Data Psychiatry clinical decision tools machine-learning neural networks neurotechnologies Neurotechnology suicidal thoughts Twitter Source Type: blogs