Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: With the increasing prevalence of Autism Spectrum Disorders (ASD), very early detection has become a key priority research topic, as early interventions can increase the chances of success. Since atypical communication is a hallmark of ASD, automated acoustic-prosodic analyses have received prominent attention. Existing studies, hover, have focused on verbal children, typically over the age of three (when many children may be reliably diagnosed) and as high as early teens. Here, an acoustic-prosodic analysis of pre-verbal vocalizations (e.g., babbles, cries) of 18-month old toddlers is performed. Data was obtained from a prospective longitudinal study looking at high-risk siblings of children with ASD who re also diagnosed with ASD, as ll as low-risk age-matched typically developing controls. Several acoustic-prosodic features re extracted and used to train support vector machine and probabilistic neural network classifiers; classification accuracy as high as 97% was obtained. Our findings suggest that markers of autism may be present in pre-verbal vocalizations of 18-month old toddlers, thus may be used to assist clinicians with very early detection of ASD.
['João Felipe Santos', 'Nirit Brosh', 'Tiago H. Falk', 'Lonnie Zwaigenbaum', 'Susan E. Bryson', 'Wendy Roberts', 'Isabel M. Smith', 'Peter Szatmari', 'Jessica Brian']
I am writing a research paper on a idea Very early detection of Autism Spectrum Disorders based on acoustic analysis of pre-verbal vocalizations of 18-month old toddlers
[{"from": "human", "value": "I am writing a research paper on a idea Very early detection of Autism Spectrum Disorders based on acoustic analysis of pre-verbal vocalizations of 18-month old toddlers"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: With the increasing prevalence of Autism Spectrum Disorders (ASD), very early detection has become a key priority research topic, as early interventions can increase the chances of success. Since atypical communication is a hallmark of ASD, automated acoustic-prosodic analyses have received prominent attention. Existing studies, hover, have focused on verbal children, typically over the age of three (when many children may be reliably diagnosed) and as high as early teens. Here, an acoustic-prosodic analysis of pre-verbal vocalizations (e.g., babbles, cries) of 18-month old toddlers is performed. Data was obtained from a prospective longitudinal study looking at high-risk siblings of children with ASD who re also diagnosed with ASD, as ll as low-risk age-matched typically developing controls. Several acoustic-prosodic features re extracted and used to train support vector machine and probabilistic neural network classifiers; classification accuracy as high as 97% was obtained. Our findings suggest that markers of autism may be present in pre-verbal vocalizations of 18-month old toddlers, thus may be used to assist clinicians with very early detection of ASD."}]