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https://hdl.handle.net/20.500.11851/713
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Özdemir, Merve Erkınay | - |
dc.contributor.author | Telatar, Ziya | - |
dc.contributor.author | Eroğul, Osman | - |
dc.contributor.author | Tunca, Yusuf | - |
dc.date.accessioned | 2019-03-15T08:12:15Z | |
dc.date.available | 2019-03-15T08:12:15Z | |
dc.date.issued | 2018-06-01 | |
dc.identifier.citation | Özdemir, M. E., Telatar, Z., Eroğul, O., & Tunca, Y. (2018). Classifying dysmorphic syndromes by using artificial neural network based hierarchical decision tree. Australasian physical & engineering sciences in medicine, 41(2), 451-461. | en_US |
dc.identifier.issn | 0158-9938 | |
dc.identifier.uri | https://doi.org/10.1007/s13246-018-0643-x | - |
dc.identifier.uri | https://hdl.handle.net/20.500.11851/713 | - |
dc.description.abstract | Dysmorphic syndromes have different facial malformations. These malformations are significant to an early diagnosis of dysmorphic syndromes and contain distinctive information for face recognition. In this study we define the certain features of each syndrome by considering facial malformations and classify Fragile X, Hurler, Prader Willi, Down, Wolf Hirschhorn syndromes and healthy groups automatically. The reference points are marked on the face images and ratios between the points’ distances are taken into consideration as features. We suggest a neural network based hierarchical decision tree structure in order to classify the syndrome types. We also implement k-nearest neighbor (k-NN) and artificial neural network (ANN) classifiers to compare classification accuracy with our hierarchical decision tree. The classification accuracy is 50, 73 and 86.7% with k-NN, ANN and hierarchical decision tree methods, respectively. Then, the same images are shown to a clinical expert who achieve a recognition rate of 46.7%. We develop an efficient system to recognize different syndrome types automatically in a simple, non-invasive imaging data, which is independent from the patient’s age, sex and race at high accuracy. The promising results indicate that our method can be used for pre-diagnosis of the dysmorphic syndromes by clinical experts. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Springer Netherlands | en_US |
dc.relation.ispartof | Australasian Physical & Engineering Sciences in Medicine | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Dysmorphic syndrome | en_US |
dc.subject | Classification | en_US |
dc.subject | Artificial neural network | en_US |
dc.subject | Hierarchical decision tree | en_US |
dc.subject | Pre diagnosis | en_US |
dc.title | Classifying Dysmorphic Syndromes by Using Artificial Neural Network Based Hierarchical Decision Tree | en_US |
dc.type | Article | en_US |
dc.department | Faculties, Faculty of Engineering, Department of Biomedical Engineering | en_US |
dc.department | Fakülteler, Mühendislik Fakültesi, Biyomedikal Mühendisliği Bölümü | tr_TR |
dc.identifier.volume | 41 | |
dc.identifier.issue | 2 | |
dc.identifier.startpage | 451 | |
dc.identifier.endpage | 461 | |
dc.authorid | 0000-0002-4640-6570 | - |
dc.identifier.wos | WOS:000433915700011 | en_US |
dc.identifier.scopus | 2-s2.0-8504616466 | en_US |
dc.institutionauthor | Eroğul, Osman | - |
dc.identifier.pmid | 29717432 | en_US |
dc.identifier.doi | 10.1007/s13246-018-0643-x | - |
dc.identifier.doi | 10.1007/s13246-018-0643-x | - |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.identifier.scopusquality | Q3 | - |
item.openairetype | Article | - |
item.languageiso639-1 | en | - |
item.grantfulltext | none | - |
item.fulltext | No Fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
crisitem.author.dept | 02.2. Department of Biomedical Engineering | - |
Appears in Collections: | Biyomedikal Mühendisliği Bölümü / Department of Biomedical Engineering PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
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