Re:A machine learning approach to identifying thought marker...
by thwee on Tuesday November 08, 2016 @09:59AM
(#12900711)
But doctors getting massive amounts of training is exactly the kind of problem computer science seeks to solve with a machine learning approach. There aren't enough doctors around to monitor every patient, so machine learning takes over. Now doctors can exactly focus on a score, and say, hey we didn't even see this.
In this case, such a tool can be used to flag behaviour automatically (Facebook does that, for instance) to start a process, i.e. have a conversation. “Depression” does not have hard-set limits, and caring about someone who had a bad day is not problematic, talking about how to deal with rejection is appropriate. Forcing them to take mind-altering substance is not ideal, but I can’t imagine any licensed doctor doing that just because some patient’s score is high, even if they do not qualify otherwise; they receive a decade of training to teach them nuance. As someone who lives with a psychiatrist, I can confirm: no one is skeptical of classification any more than the people doing the rating.
Having measuring tools (imperfect as they may be initially) is what allows science to try opposable theories, and psychiatry needs this (and plenty more tools).