We know already that people with autism have differences in brain anatomy and some regions are just bigger and smaller or just different in shape…[o]ur technique can use this information to identify someone with autism.
The study used 20 non autistic controls and 20 autistic people – all adults – and found ‘significant differences’ in the grey matter areas of the brain which control behaviour and language. This is nothing new in itself, differences in brain structure have long been known about in regards to autism. Whats new in this study is the method – and resultant accuracy – of the detection of autism.
In the experiment, Ecker showed that her imaging technique was able to detect which people in her group had autism, with 90% accuracy. “If we get a new case, we will also hopefully be 90% accurate,” she said. The research, supported by the Medical Research Council, Wellcome Trust and National Institute for Health Research, is published today in the Journal of Neuroscience .
If this is established as a viable method (Carol Povey of NAS states that further testing is still required) then it’ll be the first true objective test for autism ever developed. So far, as everyone knows, autism is diagnosed based on the opinion of a clinician (or team of specialists). Whilst they will probably still play a role, this test offers an objectivity that would be unparalleled. It would also have the interesting effect of making the DSM diagnosis largely obsolete.
Visitor:
Small point: I think "90% diagnostic accuracy" in your heading should be in quotes Kev.
Kev:
No sooner said than done ;)
Clay:
Basically, I think it's a good thing. It would be good to have objective proof, given the many errors in diagnoses currently.
Joseph:
That can't be right. I've never heard of a 90%-accurate classifier built using 40 data points.
I'm sure it's 90% accurate in the data set that was used to build it. But what this tells me is that the result is extremely over-fitted.
That's the fundamental problem with all these claims about screening accuracy.
In the future, I believe accurate screening instruments and classifiers won't come out of the conventional scientific process. They will probably come from machine learning competitions, where it's much harder to "cheat" so to speak.
Corina Becker:
It's been around the news on twitter a lot today...
A very interesting study, so I would like to see a larger study done.
According to study author Christine Ecker in today’s Guardian :
The study used 20 non autistic controls and 20 autistic people – all adults – and found ‘significant differences’ in the grey matter areas of the brain which control behaviour and language. This is nothing new in itself, differences in brain structure have long been known about in regards to autism. Whats new in this study is the method – and resultant accuracy – of the detection of autism.
If this is established as a viable method (Carol Povey of NAS states that further testing is still required) then it’ll be the first true objective test for autism ever developed. So far, as everyone knows, autism is diagnosed based on the opinion of a clinician (or team of specialists). Whilst they will probably still play a role, this test offers an objectivity that would be unparalleled. It would also have the interesting effect of making the DSM diagnosis largely obsolete.
Small point: I think "90% diagnostic accuracy" in your heading should be in quotes Kev.
No sooner said than done ;)
Basically, I think it's a good thing. It would be good to have objective proof, given the many errors in diagnoses currently.
That can't be right. I've never heard of a 90%-accurate classifier built using 40 data points. I'm sure it's 90% accurate in the data set that was used to build it. But what this tells me is that the result is extremely over-fitted. That's the fundamental problem with all these claims about screening accuracy. In the future, I believe accurate screening instruments and classifiers won't come out of the conventional scientific process. They will probably come from machine learning competitions, where it's much harder to "cheat" so to speak.
It's been around the news on twitter a lot today... A very interesting study, so I would like to see a larger study done.
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