Welcome back to Reading the Research, where I trawl the Internet to find noteworthy research on autism and related subjects, then discuss it in brief with bits from my own life, research, and observations.
Today's article is a step forward from a previously posted article. Previously, scientists and programmers had created an AI to predict what anti-depressants would help a given person, based on their brain scans. The success rate was pretty good at the time.
This technology has now advanced, and several more studies have happened. They're now giving the AI DNA tests and blood tests in addition to brain scans. More interestingly, and significantly more hopefully, they're embarking on what's called a longitudinal study, to test the long-term effectiveness of the AI's recommendations.
Longtudinal studies are ones that span years- often decades. These studies do not interfere with the participants' lives, but simply follow them across the years. The idea is to see the long-term effects of a condition like depression. In particular, these studies will assess the participants' rates and severity of depression.
The hope, of course, is that this AI is nearly infalliable and its recommendations can serve as a much quicker, more accurate, efficient psychiatrist. Instead of trying up to dozens of medications over years of depression, you would be able to submit your data to the AI, which would spit out a treatment plan. Follow the treatment plan (this medication, that form of therapy, or that type of brain stimulation) and your depression improves until perhaps you don't even qualify for the diagnosis anymore.
The reality probably won't be quite so perfect, but considering how much guessing goes into psychiatry in the first place, I feel any improvement would be good. I'll continue to keep my eye on this technology, with fingers crossed for continued good results. It's more important than ever to treat depression quickly and effectively, given the increasing rate in the general population.
(Pst! If you like seeing the latest autism-relevant research, visit my Twitter, which has links and brief comments on studies that were interesting, but didn't get a whole Reading the Research article about them.)
Today's article is a step forward from a previously posted article. Previously, scientists and programmers had created an AI to predict what anti-depressants would help a given person, based on their brain scans. The success rate was pretty good at the time.
This technology has now advanced, and several more studies have happened. They're now giving the AI DNA tests and blood tests in addition to brain scans. More interestingly, and significantly more hopefully, they're embarking on what's called a longitudinal study, to test the long-term effectiveness of the AI's recommendations.
Longtudinal studies are ones that span years- often decades. These studies do not interfere with the participants' lives, but simply follow them across the years. The idea is to see the long-term effects of a condition like depression. In particular, these studies will assess the participants' rates and severity of depression.
The hope, of course, is that this AI is nearly infalliable and its recommendations can serve as a much quicker, more accurate, efficient psychiatrist. Instead of trying up to dozens of medications over years of depression, you would be able to submit your data to the AI, which would spit out a treatment plan. Follow the treatment plan (this medication, that form of therapy, or that type of brain stimulation) and your depression improves until perhaps you don't even qualify for the diagnosis anymore.
The reality probably won't be quite so perfect, but considering how much guessing goes into psychiatry in the first place, I feel any improvement would be good. I'll continue to keep my eye on this technology, with fingers crossed for continued good results. It's more important than ever to treat depression quickly and effectively, given the increasing rate in the general population.
(Pst! If you like seeing the latest autism-relevant research, visit my Twitter, which has links and brief comments on studies that were interesting, but didn't get a whole Reading the Research article about them.)
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