There are numerous neurodevelopmental disorders, with great variability of potentially debilitating characteristics for affected individuals. However, early diagnosis is complicated by the characteristics of the subjects involved, typically in pre-school age, as in autism and dyslexia. Regarding autism, the American Academy of Pediatrics strongly insists on the necessity of diagnostic screening at least 2 times within the 2nd year of life. These indications imply the need to identify early and reliable markers, so as to improve screening. Early intervention can reduce the long periods in which the development of mental life is strongly compromised by the presence of the communicative and social defects typical of autism, and of mitigating its severity, whose full expression occurs in the first 3 years of life. Efficient screening is therefore crucial, in the hypothesis that it makes possible an early detection and treatment, such as to mitigate or even avoid the same diagnosis.
The PRIORITARIO project has developed and tested an innovative HW / SW platform for the definition of protocols for ultra-early diagnosis, analysis and therapy of neurodevelopmental disorders. To this end, university competences on distributed systems are combined with those specific to the study of neurodevelopmental disorders, possessed by the IFC-CNR. The main objective was to develop an advanced system, able to detect large volumes of data generated by the use of diagnostic tests, and to analyze them through a distributed processing system and data-mining techniques.