Full metadata record
DC Field | Value | Language |
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dc.contributor.author | Cho, Hye-Yeon | - |
dc.contributor.author | Lee, Kyungsu | - |
dc.contributor.author | Kong, Hyoun-Joong | - |
dc.contributor.author | Yang, Hyun-Lim | - |
dc.contributor.author | Jung, Chul-Woo | - |
dc.contributor.author | Park, Hee-Pyoung | - |
dc.contributor.author | Hwang, Jae Youn | - |
dc.contributor.author | Lee, Hyung-Chul | - |
dc.date.accessioned | 2022-11-17T11:40:13Z | - |
dc.date.available | 2022-11-17T11:40:13Z | - |
dc.date.created | 2022-10-26 | - |
dc.date.issued | 2023-01 | - |
dc.identifier.issn | 0003-2409 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11750/17165 | - |
dc.description.abstract | Unanticipated difficult laryngoscopy is associated with serious airway-related complications. We aimed to develop and test a convolutional neural network-based deep-learning model that uses lateral cervical spine radiographs to predict Cormack-Lehane grade 3 or 4 direct laryngoscopy views of the glottis. We analysed the radiographs of 5939 thyroid surgery patients at our hospital, 253 (4%) of whom had grade 3 or 4 glottic views. We used 10 randomly sampled datasets to train a model. We compared the new model with six similar models (VGG, ResNet, Xception, ResNext, DenseNet and SENet). The Brier score (95%CI) of the new model, 0.023 (0.021-0.025), was lower ('better') than the other models: VGG, 0.034 (0.034-0.035); ResNet, 0.033 (0.033-0.035); Xception, 0.032 (0.031-0.033); ResNext, 0.033 (0.032-0.033); DenseNet, 0.030 (0.029-0.032); SENet, 0.031 (0.029-0.032), all p < 0.001. We calculated mean (95%CI) of the new model for: R-2, 0.428 (0.388-0.468); mean squared error, 0.023 (0.021-0.025); mean absolute error, 0.048 (0.046-0.049); balanced accuracy, 0.713 (0.684-0.742); and area under the receiver operating characteristic curve, 0.965 (0.962-0.969). Radiographic features around the hyoid bone, pharynx and cervical spine were associated with grade 3 and 4 glottic views. © 2022 Association of Anaesthetists | - |
dc.language | English | - |
dc.publisher | Blackwell Publishing Inc. | - |
dc.title | Deep-learning model associating lateral cervical radiographic features with Cormack-Lehane grade 3 or 4 glottic view | - |
dc.type | Article | - |
dc.identifier.doi | 10.1111/anae.15874 | - |
dc.identifier.wosid | 000863928800001 | - |
dc.identifier.scopusid | 2-s2.0-85139198356 | - |
dc.identifier.bibliographicCitation | Anaesthesia, v.78, no.1, pp.64 - 72 | - |
dc.description.isOpenAccess | FALSE | - |
dc.subject.keywordAuthor | airway evaluation | - |
dc.subject.keywordAuthor | artificial intelligence | - |
dc.subject.keywordAuthor | deep-learning | - |
dc.subject.keywordAuthor | difficult laryngoscopy | - |
dc.subject.keywordAuthor | intratracheal | - |
dc.subject.keywordAuthor | intubation | - |
dc.subject.keywordPlus | DISTANCE | - |
dc.subject.keywordPlus | DIFFICULT INTUBATION | - |
dc.subject.keywordPlus | PREDICTION | - |
dc.subject.keywordPlus | CLASSIFICATION | - |
dc.subject.keywordPlus | METAANALYSIS | - |
dc.citation.endPage | 72 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 64 | - |
dc.citation.title | Anaesthesia | - |
dc.citation.volume | 78 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Anesthesiology | - |
dc.relation.journalWebOfScienceCategory | Anesthesiology | - |
dc.type.docType | Article | - |
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