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Collecting child psychiatry documents of clinical trials from PubMed by the SVM text classification method with the MATF weighting scheme

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dc.contributor.authorPolpinij, Jantima
dc.contributor.authorKachai, Tontrakant
dc.contributor.authorNasomboon, Kanyarat
dc.contributor.authorBheganan, Poramin
dc.contributor.editorBoonyopakorn, Pongsarun
dc.contributor.editorMeesad, Phayung
dc.contributor.editorSodsee, Sunantha
dc.contributor.editorUnger, Herwig
dc.date.accessioned2023-12-16T10:57:03Z
dc.date.available2023-12-16T10:57:03Z
dc.date.issued2020
dc.date.issuedBE2563
dc.description.abstractChild 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.
dc.identifier.doi10.1007/978-3-030-19861-9_10
dc.identifier.isbn978-3-030-19861-9
dc.identifier.urihttps://harrt.in.th/handle/123456789/8530
dc.language.isoen
dc.publisherSpringer International Publishing
dc.publisher.placeCham
dc.relation.ispartofseriesAdvances in Intelligent Systems and Computing
dc.subjectจิตเวชเด็ก
dc.subjectการทดลองคลินิค
dc.subjectการจำแนกประเภทข้อความ
dc.subjectChild Psychiatry
dc.subjectClinical Trials
dc.subjectText Classification
dc.subjectPubMed
dc.subject.isced0322 บรรณารักษ์, สารสนเทศ และการศึกษาจดหมายเหตุ
dc.subject.oecd5.8 นิเทศศาสตร์และสื่อสารมวลชน
dc.titleCollecting child psychiatry documents of clinical trials from PubMed by the SVM text classification method with the MATF weighting scheme
dc.typeเอกสารตีพิมพ์ในการประชุม (Conference Proceedings)
dspace.entity.typePublication
harrt.researchAreaสารสนเทศศาสตร์
harrt.researchGroupบรรณารักษศาสตร์และสารสนเทศศาสตร์
harrt.researchTheme.1Data Science
harrt.researchTheme.2Machine Learning
mods.location.urlhttps://link.springer.com/chapter/10.1007/978-3-030-19861-9_10
oaire.citation.endPage108
oaire.citation.startPage99
oaire.citation.titleRecent Advances in Information and Communication Technology 2019
oairecerif.author.affiliationมหาวิทยาลัยมหาสารคาม. คณะวิทยาการสารสนเทศ. ห้องปฏิบัติการเชิงปัญญา
oairecerif.event.nameIC2IT 2019: Recent Advances in Information and Communication Technology 2019
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