TY - GEN
T1 - Feature Selection Technique for Autism Spectrum Disorder
AU - Wiratsin, In On
AU - Narupiyakul, Lalita
N1 - Publisher Copyright:
© 2021 ACM.
PY - 2021/1/14
Y1 - 2021/1/14
N2 - Autism Spectrum Disorder (ASD) is a developmental disorder that restricts the development of behaviors, communication, and learning skills. People with ASD have difficulties in communicating and engaging with other people. Presently, a questionnaire called Autism Spectrum Quotient 10 (AQ-10) has been used to diagnose ASD symptoms for individuals [1]. However, using AQ-10 for ASD diagnosis is based on the observation from an individual's behavior and evaluate the result. It cannot show the outstanding attribute or relationship between ASD symptoms in different age-groups. Thus, this research proposed the novel feature selection technique for identifying the important attributes in AQ-10 results from three different age-groups, which are children at age of 7-12, adolescents at age of 13-20, and adults at age over 20. The results will represent the outstanding features and relationships between ASD symptoms in different age-groups, and lead to the proper design of ASD treatment programs for individuals.
AB - Autism Spectrum Disorder (ASD) is a developmental disorder that restricts the development of behaviors, communication, and learning skills. People with ASD have difficulties in communicating and engaging with other people. Presently, a questionnaire called Autism Spectrum Quotient 10 (AQ-10) has been used to diagnose ASD symptoms for individuals [1]. However, using AQ-10 for ASD diagnosis is based on the observation from an individual's behavior and evaluate the result. It cannot show the outstanding attribute or relationship between ASD symptoms in different age-groups. Thus, this research proposed the novel feature selection technique for identifying the important attributes in AQ-10 results from three different age-groups, which are children at age of 7-12, adolescents at age of 13-20, and adults at age over 20. The results will represent the outstanding features and relationships between ASD symptoms in different age-groups, and lead to the proper design of ASD treatment programs for individuals.
KW - Apriori algorithm
KW - Autism Spectrum Disorder screening
KW - Feature selection
UR - https://www.scopus.com/pages/publications/85101808858
U2 - 10.1145/3448218.3448241
DO - 10.1145/3448218.3448241
M3 - Conference contribution
AN - SCOPUS:85101808858
T3 - ACM International Conference Proceeding Series
SP - 53
EP - 56
BT - Proceedings - 5th International Conference on Control Engineering and Artificial Intelligence, CCEAI 2021
A2 - Zhang, Dan
PB - Association for Computing Machinery
T2 - 5th International Conference on Control Engineering and Artificial Intelligence, CCEAI 2021
Y2 - 14 January 2021 through 16 January 2021
ER -