FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4283260031> ?p ?o ?g. }

• W4283260031 abstract "The purpose of this study is to develop and evaluate the performance of a model that automatically sets a region of interest (ROI) and diagnoses mesiodens in panoramic radiographs of growing children using deep learning technology.Out of 988 panoramic radiographs, 489 patients with mesiodens were classified as an experimental group, and 499 patients without mesiodens were classified as a control group. This study consists of two networks. The first network (DeeplabV3plus) is a segmentation model that uses the posterior molar space to set the ROI in the maxillary anterior region with the mesiodens in the panoramic radiograph. The second network (Inception-resnet-v2) is a classification model that uses cropped maxillary anterior teeth to determine the presence of mesiodens. The data were divided into five groups and cross-validated. Deep learning model were created and trained using Inception-ResNet-v2. The performance of the segmentation network was evaluated using accuracy, Intersection over Union (IoU), and MeanBFscore. The overall network performance was evaluated using accuracy, precision, recall, and F1-score.Segmentation performance using posterior molar space in panoramic radiographs was 0.839, IoU 0.762, and MeanBFscore 0.907. The mean values of accuracy, precision, recall, F1-score, and area under the curve for the diagnosis of mesiodens using automatic segmentation were 0.971, 0.971, 0.971, 0.971, and 0.971, respectively.The diagnostic performance of the deep learning system using posterior molar space on the panoramic radiograph was sufficiently useful. The results of the deep learning system confirmed the possibility of complete automation of the classification of mesiodens." @default.
• W4283260031 created "2022-06-23" @default.
• W4283260031 creator A5012248556 @default.
• W4283260031 creator A5034021534 @default.
• W4283260031 creator A5037234320 @default.
• W4283260031 creator A5042369008 @default.
• W4283260031 creator A5086033312 @default.
• W4283260031 date "2022-09-01" @default.
• W4283260031 modified "2023-09-24" @default.
• W4283260031 title "Deep learning-based identification of mesiodens using automatic maxillary anterior region estimation in panoramic radiography of children" @default.
• W4283260031 cites W142666019 @default.
• W4283260031 cites W1894184971 @default.
• W4283260031 cites W1909189842 @default.
• W4283260031 cites W2000547620 @default.
• W4283260031 cites W2014877239 @default.
• W4283260031 cites W2030539839 @default.
• W4283260031 cites W2044923813 @default.
• W4283260031 cites W2091443906 @default.
• W4283260031 cites W2091695913 @default.
• W4283260031 cites W2107738186 @default.
• W4283260031 cites W2142860367 @default.
• W4283260031 cites W2156839946 @default.
• W4283260031 cites W2167277498 @default.
• W4283260031 cites W2170686637 @default.
• W4283260031 cites W2181989274 @default.
• W4283260031 cites W2402563877 @default.
• W4283260031 cites W2592929672 @default.
• W4283260031 cites W2606528214 @default.
• W4283260031 cites W2758062365 @default.
• W4283260031 cites W2800706558 @default.
• W4283260031 cites W2805714323 @default.
• W4283260031 cites W2883741661 @default.
• W4283260031 cites W2905116258 @default.
• W4283260031 cites W2908414085 @default.
• W4283260031 cites W2911333094 @default.
• W4283260031 cites W2950839012 @default.
• W4283260031 cites W2951037649 @default.
• W4283260031 cites W2951985572 @default.
• W4283260031 cites W2964309882 @default.
• W4283260031 cites W3003905048 @default.
• W4283260031 cites W3033972758 @default.
• W4283260031 cites W3195009539 @default.
• W4283260031 cites W4200220400 @default.
• W4283260031 cites W2066374605 @default.
• W4283260031 doi "https://doi.org/10.1259/dmfr.20210528" @default.
• W4283260031 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35731733" @default.
• W4283260031 hasPublicationYear "2022" @default.
• W4283260031 type Work @default.
• W4283260031 citedByCount "4" @default.
• W4283260031 countsByYear W42832600312023 @default.
• W4283260031 crossrefType "journal-article" @default.
• W4283260031 hasAuthorship W4283260031A5012248556 @default.
• W4283260031 hasAuthorship W4283260031A5034021534 @default.
• W4283260031 hasAuthorship W4283260031A5037234320 @default.
• W4283260031 hasAuthorship W4283260031A5042369008 @default.
• W4283260031 hasAuthorship W4283260031A5086033312 @default.
• W4283260031 hasConcept C108583219 @default.
• W4283260031 hasConcept C126838900 @default.
• W4283260031 hasConcept C148524875 @default.
• W4283260031 hasConcept C154945302 @default.
• W4283260031 hasConcept C199343813 @default.
• W4283260031 hasConcept C29694066 @default.
• W4283260031 hasConcept C36454342 @default.
• W4283260031 hasConcept C41008148 @default.
• W4283260031 hasConcept C71924100 @default.
• W4283260031 hasConcept C89600930 @default.
• W4283260031 hasConceptScore W4283260031C108583219 @default.
• W4283260031 hasConceptScore W4283260031C126838900 @default.
• W4283260031 hasConceptScore W4283260031C148524875 @default.
• W4283260031 hasConceptScore W4283260031C154945302 @default.
• W4283260031 hasConceptScore W4283260031C199343813 @default.
• W4283260031 hasConceptScore W4283260031C29694066 @default.
• W4283260031 hasConceptScore W4283260031C36454342 @default.
• W4283260031 hasConceptScore W4283260031C41008148 @default.
• W4283260031 hasConceptScore W4283260031C71924100 @default.
• W4283260031 hasConceptScore W4283260031C89600930 @default.
• W4283260031 hasIssue "7" @default.
• W4283260031 hasLocation W42832600311 @default.
• W4283260031 hasLocation W42832600312 @default.
• W4283260031 hasOpenAccess W4283260031 @default.
• W4283260031 hasPrimaryLocation W42832600311 @default.
• W4283260031 hasRelatedWork W2790662084 @default.
• W4283260031 hasRelatedWork W2954384599 @default.
• W4283260031 hasRelatedWork W2960184797 @default.
• W4283260031 hasRelatedWork W3094120819 @default.
• W4283260031 hasRelatedWork W3104734424 @default.
• W4283260031 hasRelatedWork W3209779739 @default.
• W4283260031 hasRelatedWork W4226289457 @default.
• W4283260031 hasRelatedWork W4285827401 @default.
• W4283260031 hasRelatedWork W4315836547 @default.
• W4283260031 hasRelatedWork W4386214304 @default.
• W4283260031 hasVolume "51" @default.
• W4283260031 isParatext "false" @default.
• W4283260031 isRetracted "false" @default.
• W4283260031 workType "article" @default.