American researchers asked a group of families to film their children interacting with objects and people. They tried Eight models of automated study To diagnose autism, which allows "streamlining the process and making it much more effective," according to the study published in Scientific Journal Plos.
The study was developed by a team of the Stanford University School of Medicine and is headed by Dennis Wall, Professor of Pediatrics and Biomedical Data Science of Californian Town.
Each of the models contained "a set of algorithms Including 5 to 12 natural characteristics of children And it produced a general score indicating whether the child had a look, "he explains.
How the videos are treated
Wall said that to evaluate the models, they asked a family to recapture the study to send home videos of one to five minutes long. In which the children's hands and hands are shown and their "social interaction as well as the use of toys, pencils and utensils" are captured.. Of the pictures, 116 youth with an average age of 4 years and 10 months were diagnosed with autism and another 46 (with an average of two years and 11 months) are developing it, he explains.
Nine expert reviews analyzed the videos using a 30 Ask Question With "yes" or "no" answers, based on typical behavior of autism, which are then incorporated into the eight mathematical models.
The best results find that 94.5% of children with autism and 77.4% of the children are identified without the authenticity. For a verification of the results they evaluated 66 other videos, Half of them from children with autism. The same model correctly identified 87.8% of the cases of children with autism and 72.7% of those who did not have the disorder.
Another advantage of using home videos for this Diagnosis Is that "they take the child in their natural environment", unlike the clinical assessment that is carried out in a device "which can be severe and artificial and cause atypical behaviors". "We have shown that we can identify a small group of natural characteristics that are highly aligned with clinical outcomes, and that non-experts can rate these characteristics quickly and independently in a virtual online environment, in minutes," said Wall.