Estimation of the Development of Depression and PTSD in Children Exposed to Sexual Abuse and Development of Decision Support Systems by Using Artificial Intelligence

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dc.authoridÖzcan, Özlem/0000-0003-3267-2648
dc.authoriducuz, ilknur/0000-0003-1986-4688
dc.authorwosidÖzcan, Özlem/ABH-9167-2020
dc.authorwosidARI, ALİ/ABH-1602-2020
dc.authorwosiducuz, ilknur/ABB-2349-2020
dc.contributor.authorUcuz, Ilknur
dc.contributor.authorAri, Ali
dc.contributor.authorOzcan, Ozlem Ozel
dc.contributor.authorTopaktas, Ozgu
dc.contributor.authorSarraf, Merve
dc.contributor.authorDogan, Ozlem
dc.date.accessioned2024-08-04T20:49:05Z
dc.date.available2024-08-04T20:49:05Z
dc.date.issued2022
dc.departmentİnönü Üniversitesien_US
dc.description.abstractThe most common diagnoses after childhood sexual abuse are Post-Traumatic Stress Disorder and depression. The aim of this study is to design a decision support system to help psychiatry physicians in the treatment of childhood sexual abuse. Computer aided decision support system (CADSS) based on ANN, which predicts the development of PTSD and Major Depressive Disorder, using different parameters of the act of abuse and patients was designed. The data of 149 girls and 21 boys who were victims of sexual abuse were included in the study. In the designed CADDS, the gender of the victim, the type of sexual abuse, the age of exposure, the duration until reporting, the time of abuse, the proximity of the abuser to the victim, number of sexual abuse, whether the child is exposed to threats and violence during the abuse, the person who reported the event, and the intelligence level of the victim are used as input parameters. The average accuracy values for all three designed systems were calculated as 99.2%. It has been shown that the system designed by using these data can be used safely in the psychiatric assessment process, in order to differentiate psychiatric diagnoses in the early post-abuse period.en_US
dc.identifier.doi10.1080/10538712.2020.1841350
dc.identifier.endpage85en_US
dc.identifier.issn1053-8712
dc.identifier.issn1547-0679
dc.identifier.issue1en_US
dc.identifier.pmid33206583en_US
dc.identifier.scopus2-s2.0-85096297734en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage73en_US
dc.identifier.urihttps://doi.org/10.1080/10538712.2020.1841350
dc.identifier.urihttps://hdl.handle.net/11616/99632
dc.identifier.volume31en_US
dc.identifier.wosWOS:000590352400001en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherRoutledge Journals, Taylor & Francis Ltden_US
dc.relation.ispartofJournal of Child Sexual Abuseen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectChildhood sexual abuseen_US
dc.subjectmachine learningen_US
dc.subjectartificial neural networksen_US
dc.subjectdepressionen_US
dc.subjectpost-traumatic stress disorderen_US
dc.titleEstimation of the Development of Depression and PTSD in Children Exposed to Sexual Abuse and Development of Decision Support Systems by Using Artificial Intelligenceen_US
dc.typeArticleen_US

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