Researchers have taken photographs of children’s retinas and screened them using a deep learning AI algorithm to diagnose autism with 100% accuracy. The findings support using AI as an objective screening tool for early diagnosis, especially when access to a specialist child psychiatrist is limited.
  • bionicjoey@lemmy.caEnglish
    1·
    7 months ago

    It worries me that this research came out of South Korea; A country which I’ve heard is particularly stigmatizing of neurodivergence

  • Deestan@lemmy.worldEnglish
    1·
    7 months ago

    A full 100% sounds weird. It means complete overlap with the ASD assessment which itself isn’t bulletproof. Weird like there were some mistakes in the data. E.g. all ASD pictures taken on the same day and getting a date timestamp, “ASD” written in the metadata or filename, or different light in different lab.

    I didn’t see any immediate problems in the published paper, but if these were my results I’d be to worried to publish it.

    • sosodev@lemmy.worldEnglish
      2·
      7 months ago

      It sounds like the model is overfitting the training data. They say it scored 100% on the testing set of data which almost always indicates that the model has learned how to ace the training set but flops in the real world.

      I think we shouldn’t put much weight behind this news article. This is just more overblown hype for the sake of clicks.

  • Bouchtroubouli@lemmy.worldEnglish
    1·
    7 months ago

    Well, 100% accuracy after removing all the noise in the dataset …

    At least it proves that their method can separate two extremes. But what about the real life where 90% of the people are ?

  • vzq@lemmy.blahaj.zoneEnglish
    0·
    7 months ago

    False negatives is what freaks me out. Sorry bud, magic machine says you’re not really autistic. No adaptions or special school for you. Good luck out there.

      • Krzak@discuss.onlineEnglish
        1·
        7 months ago

        It’s easier to reason with a doctor than a computer. I can imagine you’d be in the system for good after such “evaluation” so it could mean slim chances of retesting