TY - GEN
T1 - Collecting Child Psychiatry Documents of Clinical Trials from PubMed by the SVM Text Classification Method with the MATF Weighting Scheme
AU - Polpinij, Jantima
AU - Kachai, Tontrakant
AU - Nasomboon, Kanyarat
AU - Bheganan, Poramin
N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - Child psychiatry is a branch of psychiatry focused on the diagnosis, treatment, and prevention of mental health issues in children and their families. In many countries, the study of disorders such as ADHD (Attention-Deficit/Hyperactivity Disorder) by child and adolescent psychiatry is still in its infancy, with the result that children’s mental health issues can be the source of embarrassment for the family and of shame for many children. Misunderstanding, denying, and ignoring children’s mental health issues by parents are the main problem encountered in diagnosis and treatment of mental health issues in children. To help parents and extended families understand this problem better, and thus help them to better care for children with mental health issues, starting with seeking help from a psychiatrist without embarrassment, an easily accessible and reliable source of information is urgently needed. To develop such a single source of information, relevant documents need to be gathered together. This study presents a method of gathering reports of clinical trials from PubMed which describe diagnosis and treatment of child mental health issues. The main mechanism of the proposed method is a Support Vector Machine with a Multi Aspect TF (MATF) weighting scheme. After testing by recall, precision, and F1, it can return satisfactory results of 0.82, 0.79, and 0.80 respectively.
AB - Child psychiatry is a branch of psychiatry focused on the diagnosis, treatment, and prevention of mental health issues in children and their families. In many countries, the study of disorders such as ADHD (Attention-Deficit/Hyperactivity Disorder) by child and adolescent psychiatry is still in its infancy, with the result that children’s mental health issues can be the source of embarrassment for the family and of shame for many children. Misunderstanding, denying, and ignoring children’s mental health issues by parents are the main problem encountered in diagnosis and treatment of mental health issues in children. To help parents and extended families understand this problem better, and thus help them to better care for children with mental health issues, starting with seeking help from a psychiatrist without embarrassment, an easily accessible and reliable source of information is urgently needed. To develop such a single source of information, relevant documents need to be gathered together. This study presents a method of gathering reports of clinical trials from PubMed which describe diagnosis and treatment of child mental health issues. The main mechanism of the proposed method is a Support Vector Machine with a Multi Aspect TF (MATF) weighting scheme. After testing by recall, precision, and F1, it can return satisfactory results of 0.82, 0.79, and 0.80 respectively.
KW - ADHD
KW - Child psychiatry
KW - Clinical trials
KW - Multi Aspect TF
KW - PubMed
KW - Support Vector Machines
KW - Text classification
UR - https://www.scopus.com/pages/publications/85065916379
U2 - 10.1007/978-3-030-19861-9_10
DO - 10.1007/978-3-030-19861-9_10
M3 - Conference contribution
AN - SCOPUS:85065916379
SN - 9783030198602
T3 - Advances in Intelligent Systems and Computing
SP - 99
EP - 108
BT - Recent Advances in Information and Communication Technology 2019 - Proceedings of the 15th International Conference on Computing and Information Technology IC2IT 2019
A2 - Unger, Herwig
A2 - Boonyopakorn, Pongsarun
A2 - Meesad, Phayung
A2 - Sodsee, Sunantha
PB - Springer Verlag
T2 - 15th International Conference on Computing and Information Technology, IC2IT 2019
Y2 - 4 July 2019 through 5 July 2019
ER -