Latest AI and machine learning research in autism for healthcare professionals.
Although it has often been argued that clinical applications of advanced technology may hold promise for addressing impairments associated with autism spectrum disorder (ASD), relatively few investigations have indexed the impact of intervention and feedback approaches. This pilot study investigated the application of a novel robotic interaction system capable of administering and adjusting joint ...
The aim of the study was to investigate the effectiveness of a brief robot-mediated intervention based on Lego(®) therapy on improving collaborative behaviors (i.e., interaction initiations, responses, and play together) between children with ASD and their siblings during play sessions, in a therapeutic setting. A concurrent multiple baseline design across three child-sibling pairs was in effect. ...
Children with autism spectrum disorder (ASD) engage in highly perseverative and inflexible behaviours. Technological tools, such as robots, received i...
In the present work, we have undertaken a proof-of-concept study to determine whether a simple upper-limb movement could be useful to accurately class...
Machine learning has immense potential to enhance diagnostic and intervention research in the behavioral sciences, and may be especially useful in inv...
Multivariate pattern analysis (MVPA) methods have become an important tool in neuroimaging, revealing complex associations and yielding powerful predi...
Here we introduce artificial intelligence (AI) methodology for detecting and characterizing epistasis in genetic association studies. The ultimate goa...
The quality of potato is directly related to their edible value and industrial value. Hollow heart of potato, as a physiological disease occurred insi...
We present a new genetic filter to identify a predictive gene subset for cancer-type classification on gene expression profiles. This approach pursues...