Building Language Resources for Exploring Autism Spectrum Disorders
Autism spectrum disorder (ASD) is a complex neurodevelopmental condition that would benefit from low-cost and reliable improvements to screening and diagnosis. Human language technologies (HLTs) provide one possible route to automating a series of subjective decisions that currently inform {``}Gold Standard{''} diagnosis based on clinical judgment. In this paper, we describe a new resource to support this goal, comprised of 100 20-minute semi-structured English language samples labeled with child age, sex, IQ, autism symptom severity, and diagnostic classification. We assess the feasibility of digitizing and processing sensitive clinical samples for data sharing, and identify areas of difficulty. Using the methods described here, we propose to join forces with researchers and clinicians throughout the world to establish an international repository of annotated language samples from individuals with ASD and related disorders. This project has the potential to improve the lives of individuals with ASD and their families by identifying linguistic features that could improve remote screening, inform personalized intervention, and promote advancements in clinically-oriented HLTs.
Code (0)
등록된 구현이 없습니다.
Tasks
DiagnosticSimilar Papers 제목 키워드 기반
Exploring Autism Spectrum Disorders Using HLT
NeuRO: An Application for Code-Switched Autism Detection in Children
Code-switching is a common communication phenomenon where individuals alternate between two or more languages or linguistic styles within a single conversation. Autism Spectrum Disorder (ASD) is a developmental disorder …
Autism detectionFormulatic Language of Vietnamese Children with Autism Spectrum Disorders: A Corpus Linguistic Analysis
Exploring Neurofunctional Phase Transition Patterns in Autism Spectrum Disorder: A Thermodynamics Parameters Analysis Approach
Designing network parameters that can effectively represent complex networks is of significant importance for the analysis of time-varying complex networks. This paper introduces a novel thermodynamic framework for analy…
Exploring the pattern of Emotion in children with ASD as an early biomarker through Recurring-Convolution Neural Network (R-CNN)
Autism Spectrum Disorder (ASD) is found to be a major concern among various occupational therapists. The foremost challenge of this neurodevelopmental disorder lies in the fact of analyzing and exploring various symptoms…