Dataset for Autism Diagnosis Based on DSM-5

Published: 6 December 2022| Version 1 | DOI: 10.17632/749k3cwbnm.1
Contributors:
Umar A Ibrahim,

Description

Autism is a neurodevelopmental condition affecting individuals from childhood up to adulthood. Individuals living with Autism are said to be having challenges with cognitive, social, and communication skills. According to the DSM5 criteria, there are 3 levels of Autism: Level 1, Level 2, and Level 3. Knowing the severity level of an individual after diagnosis helps in providing the right therapy for the individual. Most research work has focused on the diagnosis of autism, as in discriminating autistic individuals from non-autistic individuals. Very few works have been done in classifying autism into its severity levels based on the DSM 5 criteria. In this study, we collected datasets from individuals based on the guidelines of the DSM5 criteria using the google forms questionnaire.

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Steps to reproduce

First, we started by creating a questionnaire that has the following features: Age, Gender, age of mother, status eg, parent, teacher or caretaker, was the child formerly diagnosed or not, DSM level, age when the child was diagnosed, and country where the child was diagnosed. Next, this questionnaire was shared among, teachers, parents, and caretakers. The responders' details were not collected for data privacy. collected datasets were then organized, and incomplete answers were deleted.

Categories

Machine Learning, Autism, Autism Spectrum Disorder, Childhood Autism, Patient with Autism Spectrum Disorder

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