| Autor: |
Young Ho Kim, Inhwan Kim, Yoon-Ji Kim, Minji Kim, Jin-Hyoung Cho, Mihee Hong, Kyung-Hwa Kang, Sung-Hoon Lim, Su-Jung Kim, Namkug Kim, Jeong Won Shin, Sang-Jin Sung, Seung-Hak Baek, Hwa Sung Chae |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Scientific Reports, Vol 13, Iss 1, Pp 1-10 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2045-2322 |
| DOI: |
10.1038/s41598-023-44207-2 |
| Popis: |
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 |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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