{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T19:13:18Z","timestamp":1778872398754,"version":"3.51.4"},"reference-count":40,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2025,6,13]],"date-time":"2025-06-13T00:00:00Z","timestamp":1749772800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Dental Traumatology"],"published-print":{"date-parts":[[2025,12]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aim<\/jats:title>\n                    <jats:p>To analyze the characteristics of pediatric facial trauma and predict factors influencing them through machine learning algorithms.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Material and Methods<\/jats:title>\n                    <jats:p>A prospective hospital\u2010based study was carried out between January 2024 and January 2025. All patients up to 15\u2009years of age reporting with maxillofacial trauma formed the sample. Collected data was subjected to logistic regression analysis and machine learning algorithms (Bayesian Network, CHAID and Neural Network) to determine factors influencing pediatric maxillofacial trauma.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Logistic regression and Bayesian Network demonstrated 92.59% accuracy, whereas CHAID and Neural Network showed an accuracy of 78.40% and 74.69%, respectively. Bayesian Network and Logistic Regression with similar accuracy showed age (21.77%), (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.014) as the variable with maximum predictor importance, followed by paternal education (15.65%), (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.003), maternal education (12.55%), (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.040) and parental employment (9.43%), (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.040). Further, Bayesian Network showed RTA (9.66%), sex (6.36%), maxillofacial fracture treatment (5.99%), other causes of trauma (5.67%), religion (2.89%) and delay in TDI treatment (2.78%) as other predictor variables. Parental employment had the maximum predictor importance (17.36%) in the Neural Network, whereas maternal education demonstrated the highest predictor importance (33.03%) in the CHAID model.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Age showed highest importance in predicting maxillofacial trauma when machine learning algorithms were used, followed by parental education and employment as other major predictors which suggested that children from lower socioeconomic status were more prone to trauma, as employment serves as a proxy for education.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/edt.13077","type":"journal-article","created":{"date-parts":[[2025,6,13]],"date-time":"2025-06-13T08:39:17Z","timestamp":1749803957000},"page":"687-695","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Pediatric Maxillofacial Trauma: Machine Learning Based Predictive Modeling to Identify Trauma Patterns"],"prefix":"10.1111","volume":"41","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-5660-8425","authenticated-orcid":false,"given":"Elsy","family":"Antony","sequence":"first","affiliation":[{"name":"Department of Pediatric and Preventive Dentistry, Dr. Ziauddin Ahmad Dental College Aligarh Muslim University  Aligarh India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Saima Yunus","family":"Khan","sequence":"additional","affiliation":[{"name":"Department of Pediatric and Preventive Dentistry, Dr. Ziauddin Ahmad Dental College Aligarh Muslim University  Aligarh India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Md Kalim","family":"Ansari","sequence":"additional","affiliation":[{"name":"Department of Oral and Maxillofacial Surgery, Dr. Ziauddin Ahmad Dental College Aligarh Muslim University  Aligarh India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Divya Sanjay","family":"Sharma","sequence":"additional","affiliation":[{"name":"Department of Pediatric and Preventive Dentistry, Dr. Ziauddin Ahmad Dental College Aligarh Muslim University  Aligarh India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Manoj Kumar","family":"Sharma","sequence":"additional","affiliation":[{"name":"I.T.S College of Pharmacy  Ghaziabad Uttar Pradesh India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2025,6,13]]},"reference":[{"key":"e_1_2_12_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.injury.2020.04.053"},{"key":"e_1_2_12_3_1","doi-asserted-by":"publisher","DOI":"10.4236\/ojo.2022.126027"},{"key":"e_1_2_12_4_1","doi-asserted-by":"publisher","DOI":"10.5005\/jp-journals-10005-1687"},{"key":"e_1_2_12_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12663-022-01842-y"},{"key":"e_1_2_12_6_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12663-009-0037-4"},{"key":"e_1_2_12_7_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10006-021-00966-8"},{"key":"e_1_2_12_8_1","doi-asserted-by":"publisher","DOI":"10.1017\/ash.2021.192"},{"key":"e_1_2_12_9_1","doi-asserted-by":"publisher","DOI":"10.5005\/jp-journals-10005-2905"},{"key":"e_1_2_12_10_1","doi-asserted-by":"publisher","DOI":"10.4103\/jisppd.jisppd_50_24"},{"key":"e_1_2_12_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijin.2022.05.002"},{"key":"e_1_2_12_12_1","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCOUTCOMES.120.006556"},{"key":"e_1_2_12_13_1","doi-asserted-by":"publisher","DOI":"10.1093\/cid\/cix731"},{"key":"e_1_2_12_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jval.2019.01.006"},{"key":"e_1_2_12_15_1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2013.281053"},{"key":"e_1_2_12_16_1","first-page":"591","volume-title":"Rowe and Williams' Maxillofacial Injuries","author":"Bowerman J. 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