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The prediction of sagittal chin point relapse following two-jaw surgery using machine learning
DC Field | Value | Language |
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dc.contributor.author | Kim, YH | - |
dc.contributor.author | Kim, I | - |
dc.contributor.author | Kim, YJ | - |
dc.contributor.author | Ki, M | - |
dc.contributor.author | Cho, JH | - |
dc.contributor.author | Hong, M | - |
dc.contributor.author | Kang, KH | - |
dc.contributor.author | Lim, SH | - |
dc.contributor.author | Kim, SJ | - |
dc.contributor.author | Kim, N | - |
dc.contributor.author | Shin, JW | - |
dc.contributor.author | Sung, SJ | - |
dc.contributor.author | Baek, SH | - |
dc.contributor.author | Chae, HS | - |
dc.date.accessioned | 2023-11-09T05:00:33Z | - |
dc.date.available | 2023-11-09T05:00:33Z | - |
dc.date.issued | 2023 | - |
dc.identifier.uri | http://repository.ajou.ac.kr/handle/201003/26518 | - |
dc.description.abstract | The study aimed to identify critical factors associated with the surgical stability of pogonion (Pog) by applying machine learning (ML) to predict relapse following two-jaw orthognathic surgery (2 J-OGJ). The sample set comprised 227 patients (110 males and 117 females, 207 training and 20 test sets). Using lateral cephalograms taken at the initial evaluation (T0), pretreatment (T1), after (T2) 2 J-OGS, and post treatment (T3), 55 linear and angular skeletal and dental surgical movements (T2-T1) were measured. Six ML modes were utilized, including classification and regression trees (CART), conditional inference tree (CTREE), and random forest (RF). The training samples were classified into three groups; highly significant (HS) (≥ 4), significant (S) (≥ 2 and < 4), and insignificant (N), depending on Pog relapse. RF indicated that the most important variable that affected relapse rank prediction was ramus inclination (RI), CTREE and CART revealed that a clockwise rotation of more than 3.7 and 1.8 degrees of RI was a risk factor for HS and S groups, respectively. RF, CTREE, and CART were practical tools for predicting surgical stability. More than 1.8 degrees of CW rotation of the ramus during surgery would lead to significant Pog relapse. | - |
dc.language.iso | en | - |
dc.subject.MESH | Cephalometry | - |
dc.subject.MESH | Chin | - |
dc.subject.MESH | Female | - |
dc.subject.MESH | Follow-Up Studies | - |
dc.subject.MESH | Humans | - |
dc.subject.MESH | Male | - |
dc.subject.MESH | Malocclusion, Angle Class III | - |
dc.subject.MESH | Mandible | - |
dc.subject.MESH | Maxilla | - |
dc.subject.MESH | Orthognathic Surgical Procedures | - |
dc.subject.MESH | Recurrence | - |
dc.subject.MESH | Retrospective Studies | - |
dc.title | The prediction of sagittal chin point relapse following two-jaw surgery using machine learning | - |
dc.type | Article | - |
dc.identifier.pmid | 37813915 | - |
dc.identifier.url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10562368 | - |
dc.contributor.affiliatedAuthor | Kim, YH | - |
dc.contributor.affiliatedAuthor | Shin, JW | - |
dc.type.local | Journal Papers | - |
dc.identifier.doi | 10.1038/s41598-023-44207-2 | - |
dc.citation.title | Scientific reports | - |
dc.citation.volume | 13 | - |
dc.citation.number | 1 | - |
dc.citation.date | 2023 | - |
dc.citation.startPage | 17005 | - |
dc.citation.endPage | 17005 | - |
dc.identifier.bibliographicCitation | Scientific reports, 13(1). : 17005-17005, 2023 | - |
dc.identifier.eissn | 2045-2322 | - |
dc.relation.journalid | J020452322 | - |
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