Diagnostic accuracy of convolutional neural network algorithms to distinguish gastrointestinal obstruction on conventional radiographs in a pediatric population.

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Title: Diagnostic accuracy of convolutional neural network algorithms to distinguish gastrointestinal obstruction on conventional radiographs in a pediatric population.
Authors: Ayaz E; Diyarbakır Children's Hospital, Radiology Clinic, Diyarbakır; Current: University of Health Sciences Türkiye, Başakşehir Çam and Sakura City Hospital, Department of Radiology, İstanbul, Türkiye., Güçlü H; İstanbul Medeniyet University Faculty of Engineering and Natural Sciences, Department of Biostatistics and Medical Informatics, İstanbul; Current: TOBB University of Economics and Technology, Department of Artificial Intelligence Engineering, Ankara, Türkiye., Oktay AB; Yıldız Technical University Faculty of Engineering, Department of Computer Engineering, İstanbul, Türkiye.
Source: Diagnostic and interventional radiology (Ankara, Turkey) [Diagn Interv Radiol] 2026 Mar 02; Vol. 32 (2), pp. 233-241. Date of Electronic Publication: 2025 Feb 28.
Publication Type: Journal Article
Journal Info: Publisher: Galenos Publishing House Country of Publication: Turkey NLM ID: 101241152 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1305-3612 (Electronic) Linking ISSN: 13053825 NLM ISO Abbreviation: Diagn Interv Radiol Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: Diagnostic accuracy of convolutional neural network algorithms to distinguish gastrointestinal obstruction on conventional radiographs in a pediatric population.
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  Data: <searchLink fieldCode="AU" term="%22Ayaz+E%22">Ayaz E</searchLink>; Diyarbakır Children's Hospital, Radiology Clinic, Diyarbakır; Current: University of Health Sciences Türkiye, Başakşehir Çam and Sakura City Hospital, Department of Radiology, İstanbul, Türkiye.<br /><searchLink fieldCode="AU" term="%22Güçlü+H%22">Güçlü H</searchLink>; İstanbul Medeniyet University Faculty of Engineering and Natural Sciences, Department of Biostatistics and Medical Informatics, İstanbul; Current: TOBB University of Economics and Technology, Department of Artificial Intelligence Engineering, Ankara, Türkiye.<br /><searchLink fieldCode="AU" term="%22Oktay+AB%22">Oktay AB</searchLink>; Yıldız Technical University Faculty of Engineering, Department of Computer Engineering, İstanbul, Türkiye.
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  Data: <searchLink fieldCode="JN" term="%22101241152%22">Diagnostic and interventional radiology (Ankara, Turkey)</searchLink> [Diagn Interv Radiol] 2026 Mar 02; Vol. 32 (2), pp. 233-241. <i>Date of Electronic Publication: </i>2025 Feb 28.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Galenos+Publishing+House%22">Galenos Publishing House </searchLink><i>Country of Publication: </i>Turkey <i>NLM ID: </i>101241152 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1305-3612 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2213053825%22">13053825 </searchLink><i>NLM ISO Abbreviation: </i>Diagn Interv Radiol <i>Subsets: </i>MEDLINE
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        Value: 10.4274/dir.2025.242950
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      – Code: eng
        Text: English
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        StartPage: 233
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      – TitleFull: Diagnostic accuracy of convolutional neural network algorithms to distinguish gastrointestinal obstruction on conventional radiographs in a pediatric population.
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            NameFull: Ayaz E
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            NameFull: Güçlü H
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            – D: 02
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              Text: 2026 Mar 02
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              Y: 2026
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