{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,28]],"date-time":"2026-10-28T12:43:40Z","timestamp":1793191420070,"version":"4.5.0"},"reference-count":40,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2025,1,25]],"date-time":"2025-01-25T00:00:00Z","timestamp":1737763200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Tel Aviv University"},{"name":"Orthodontic Research Center"},{"name":"University Hospital of Regensburg"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"abstract":"<jats:p>Background: Orthodontic problems can affect vital quality of life functions, such as swallowing, speech sound production, and the aesthetic effect. Therefore, it is important to diagnose and treat these patients precisely. The main aim of this study is to introduce new classification methods for skeletal class I occlusion (SCIO) and skeletal class II malocclusion (SCIIMO) among Arab patients in Israel. We conducted hierarchical clustering to detect critical trends within malocclusion classes and applied machine learning (ML) models to predict classification outcomes. Methods: This study is based on assessing the lateral cephalometric parameters from the Center for Dentistry Research and Aesthetics based in Jatt, Israel. The study involved the encoded records of 394 Arab patients with diagnoses of SCIO\/SCIIMO, according to the individualized ANB of Panagiotidis and Witt. After clustering analysis, an ML model was established by evaluating the performance of different models. Results: The clustering analysis identified three distinct clusters for each skeletal class (SCIO and SCIIMO). Among SCIO clusters, the results showed that in the second cluster, retrognathism of the mandible was less severe, as represented by a lower ANB angle. In addition, the third cluster had a lower NL-ML angle, gonial angle, SN-Ba angle, and lower ML-NSL angle compared to clusters 1 and 2. Among SCIIMO clusters, the results also showed that the second cluster has less severe retrognathism of the mandible, which is represented by a lower ANB angle and Calculated_ANB and a higher SNB angle (p &lt; 0.05). The general ML model that included all measurements for patient classification showed a classification accuracy of 0.87 in the Random Forest and the Classification and Regression Tree models. Using ANB angle and Wits appraisal only in the ML, an accuracy of 0.78 (sensitivity = 0.80, specificity = 0.76) was achieved to classify patients as SCIO or SCIIMO. Conclusions: The clustering analysis revealed distinguished patterns that can be present within SCIO and SCIIMO patients, which can affect the diagnosis and treatment plan. In addition, the ML model can accurately diagnose SCIO\/SCIIMO patients, which should improve precise diagnostics.<\/jats:p>","DOI":"10.3390\/jcm14030792","type":"journal-article","created":{"date-parts":[[2025,1,28]],"date-time":"2025-01-28T07:54:08Z","timestamp":1738050848000},"page":"792","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Clustering and Machine Learning Models of Skeletal Class I and II Parameters of Arab Orthodontic Patients"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0144-575X","authenticated-orcid":false,"given":"Kareem","family":"Midlej","sequence":"first","affiliation":[{"name":"Department of Clinical Microbiology and Immunology, Faculty of Medicine and Health Sciences, Tel Aviv University, Tel Aviv 6997801, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3530-1420","authenticated-orcid":false,"given":"Osayd","family":"Zohud","sequence":"additional","affiliation":[{"name":"Department of Clinical Microbiology and Immunology, Faculty of Medicine and Health Sciences, Tel Aviv University, Tel Aviv 6997801, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5292-6778","authenticated-orcid":false,"given":"Iqbal M.","family":"Lone","sequence":"additional","affiliation":[{"name":"Department of Clinical Microbiology and Immunology, Faculty of Medicine and Health Sciences, Tel Aviv University, Tel Aviv 6997801, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-9808-2468","authenticated-orcid":false,"given":"Obaida","family":"Awadi","sequence":"additional","affiliation":[{"name":"Center for Dentistry Research and Aesthetics, Jatt 4491800, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-6848-8753","authenticated-orcid":false,"given":"Samir","family":"Masarwa","sequence":"additional","affiliation":[{"name":"Center for Dentistry Research and Aesthetics, Jatt 4491800, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eva","family":"Paddenberg-Schubert","sequence":"additional","affiliation":[{"name":"Department of Orthodontics, University Hospital of Regensburg, University of Regensburg, 93047 Regensburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sebastian","family":"Krohn","sequence":"additional","affiliation":[{"name":"Department of Orthodontics, University Hospital of Regensburg, University of Regensburg, 93047 Regensburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christian","family":"Kirschneck","sequence":"additional","affiliation":[{"name":"Department of Orthodontics, University of Bonn, 53111 Bonn, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peter","family":"Proff","sequence":"additional","affiliation":[{"name":"Department of Orthodontics, University Hospital of Regensburg, University of Regensburg, 93047 Regensburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-3924-0327","authenticated-orcid":false,"given":"Nezar","family":"Watted","sequence":"additional","affiliation":[{"name":"Center for Dentistry Research and Aesthetics, Jatt 4491800, Israel"},{"name":"Department of Orthodontics, Faculty of Dentistry, Arab America University, Jenin 919000, Palestine"},{"name":"Gathering for Prosperity Initiative, Jatt 4491800, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5525-206X","authenticated-orcid":false,"given":"Fuad A.","family":"Iraqi","sequence":"additional","affiliation":[{"name":"Department of Clinical Microbiology and Immunology, Faculty of Medicine and Health Sciences, Tel Aviv University, Tel Aviv 6997801, Israel"},{"name":"Department of Orthodontics, University Hospital of Regensburg, University of Regensburg, 93047 Regensburg, Germany"},{"name":"Gathering for Prosperity Initiative, Jatt 4491800, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,1,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Lone, I.M., Zohud, O., Midlej, K., Proff, P., Watted, N., and Iraqi, F.A. (2023). Skeletal Class II Malocclusion: From Clinical Treatment Strategies to the Roadmap in Identifying the Genetic Bases of Development in Humans with the Support of the Collaborative Cross Mouse Population. J. Clin. Med., 12.","DOI":"10.3390\/jcm12155148"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Lone, I.M., Zohud, O., Nashef, A., Kirschneck, C., Proff, P., Watted, N., and Iraqi, F.A. (2023). Dissecting the Complexity of Skeletal-Malocclusion-Associated Phenotypes: Mouse for the Rescue. Int. J. Mol. Sci., 24.","DOI":"10.3390\/ijms24032570"},{"key":"ref_3","unstructured":"Ghodasra, R., and Brizuela, M. (2023). Orthodontics, Malocclusion. StatPearls, StatPearls Publishing."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Francisco, I., Ribeiro, M.P., Marques, F., Travassos, R., Nunes, C., Pereira, F., Caramelo, F., Paula, A.B., and Vale, F. (2022). Application of Three-Dimensional Digital Technology in Orthodontics: The State of the Art. Biomimetics, 7.","DOI":"10.3390\/biomimetics7010023"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Zohud, O., Lone, I.M., Midlej, K., Obaida, A., Masarwa, S., Schr\u00f6der, A., K\u00fcchler, E.C., Nashef, A., Kassem, F., and Reiser, V. (2023). Towards Genetic Dissection of Skeletal Class III Malocclusion: A Review of Genetic Variations Underlying the Phenotype in Humans and Future Directions. J. Clin. Med., 12.","DOI":"10.3390\/jcm12093212"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Watted, N., Lone, I.M., Midlej, K., Zohud, O., Awadi, O., Masarwa, S., Watted, A., Paddenberg, E., Krohn, S., and Kirschneck, C. (2024). The Complexity of Skeletal Transverse Dimension: From Diagnosis, Management, and Treatment Strategies to the Application of Collaborative Cross (CC) Mouse Model. J. Funct. Morphol. Kinesiol., 9.","DOI":"10.20944\/preprints202401.1123.v1"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Cenzato, N., Nobili, A., and Maspero, C. (2021). Prevalence of Dental Malocclusions in Different Geographical Areas: Scoping Review. Dent. J., 9.","DOI":"10.3390\/dj9100117"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Lone, I.M., Zohud, O., Midlej, K., Awadi, O., Masarwa, S., Krohn, S., Kirschneck, C., Proff, P., Watted, N., and Iraqi, F.A. (2023). Narrating the Genetic Landscape of Human Class I Occlusion: A Perspective-Infused Review. J. Pers. Med., 13.","DOI":"10.3390\/jpm13101465"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"729","DOI":"10.1016\/0002-9416(53)90082-7","article-title":"Cephalometrics for You and Me","volume":"39","author":"Steiner","year":"1953","journal-title":"Am. J. Orthod."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"195","DOI":"10.2319\/071917-482.1","article-title":"Dental Anomalies in Different Growth and Skeletal Malocclusion Patterns","volume":"88","author":"Luiz","year":"2018","journal-title":"Angle Orthod."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1016\/S0002-9416(76)90318-3","article-title":"Application of the \u201cWits\u201d Appraisal","volume":"70","author":"Jacobson","year":"1976","journal-title":"Am. J. Orthod."},{"key":"ref_12","first-page":"S267","article-title":"THE CORRELATION BETWEEN WITS AND ANB CEPHALOMETRIC LANDMARKS IN ORTHODONTIC PATEINTS","volume":"67","author":"Armed","year":"2017","journal-title":"Pak. Armed Forces Med. J."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"408","DOI":"10.1007\/BF02163219","article-title":"Der Individualisierte ANB-Winkel","volume":"38","author":"Panagiotidis","year":"1977","journal-title":"Fortschr. Kieferorthop."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"383","DOI":"10.1016\/0889-5406(86)90004-1","article-title":"Floating Norms for the ANB Angle as Guidance for Clinical Considerations","volume":"90","year":"1986","journal-title":"Am. J. Orthod. Dentofac. Orthop."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"432","DOI":"10.1016\/0889-5406(88)90134-5","article-title":"Relation of the Wits Appraisal to the ANB Angle: A Statistical Appraisal","volume":"94","year":"1988","journal-title":"Am. J. Orthod. Dentofac. Orthop."},{"key":"ref_16","first-page":"449","article-title":"The Individualized ANB Angle of Chinese Adults","volume":"6","author":"Yen","year":"1990","journal-title":"Kaohsiung J. Med. Sci."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1007\/s00056-021-00322-1","article-title":"Floating Norms for Individualising the ANB Angle and the WITS Appraisal in Orthodontic Cephalometric Analysis Based on Guiding Variables","volume":"84","author":"Paddenberg","year":"2023","journal-title":"J. Orofac. Orthop."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1065","DOI":"10.17219\/acem\/138702","article-title":"Machine Learning in Orthodontics: Challenges and Perspectives","volume":"30","author":"Liu","year":"2021","journal-title":"Adv. Clin. Exp. Med."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"159.e1","DOI":"10.1016\/j.forsciint.2015.12.025","article-title":"An Automatic Method for Skeletal Patterns Classification Using Craniomaxillary Variables on a Colombian Population","volume":"261","author":"Jaque","year":"2016","journal-title":"Forensic Sci. Int."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1177\/0022034520901715","article-title":"Automated Skeletal Classification with Lateral Cephalometry Based on Artificial Intelligence","volume":"99","author":"Yu","year":"2020","journal-title":"J. Dent. Res."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1391","DOI":"10.1016\/j.joms.2023.07.137","article-title":"Novel Machine Learning Algorithms for Prediction of Treatment Decisions in Adult Patients with Class III Malocclusion","volume":"81","author":"Taraji","year":"2023","journal-title":"J. Oral Maxillofac. Surg."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1186\/s40510-021-00361-9","article-title":"Applications of Artificial Intelligence and Machine Learning in Orthodontics: A Scoping Review","volume":"22","author":"Bichu","year":"2021","journal-title":"Prog. Orthod."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Nielsen, F. (2016). Introduction to HPC with MPI for Data Science, Springer.","DOI":"10.1007\/978-3-319-21903-5"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1007\/s00357-014-9161-z","article-title":"Ward\u2019s Hierarchical Agglomerative Clustering Method: Which Algorithms Implement Ward\u2019s Criterion?","volume":"31","author":"Murtagh","year":"2014","journal-title":"J. Classif."},{"key":"ref_25","first-page":"48","article-title":"Package \u201cCaret\u201d","volume":"223","author":"Kuhn","year":"2020","journal-title":"R J."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Xanthopoulos, P., Pardalos, P.M., and Trafalis, T.B. (2013). Robust Data Mining, Springer.","DOI":"10.1007\/978-1-4419-9878-1"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1007\/BF00994018","article-title":"Support-Vector Networks","volume":"20","author":"Cortes","year":"1995","journal-title":"Mach. Learn."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Pisner, D.A., and Schnyer, D.M. (2020). Support Vector Machine. Machine Learning: Methods and Applications to Brain Disorders, Academic Press.","DOI":"10.1016\/B978-0-12-815739-8.00006-7"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1109\/TIT.1967.1053964","article-title":"Nearest Neighbor Pattern Classification","volume":"13","author":"Cover","year":"1967","journal-title":"IEEE Trans. Inf. Theory"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Qahaz, N., Lone, I.M., Khadija, A., Ghnaim, A., Zohud, O., Ben Nun, N., Nashef, A., Abu El-Naaj, I., and Iraqi, F.A. (2023). Host Genetic Background Effect on Body Weight Changes Influenced by Heterozygous Smad4 Knockout Using Collaborative Cross Mouse Population. Int. J. Mol. Sci., 24.","DOI":"10.20944\/preprints202309.2084.v1"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1002\/ame2.12311","article-title":"High-Fat Diet and Oral Infection Induced Type 2 Diabetes and Obesity Development under Different Genetic Backgrounds","volume":"6","author":"Lone","year":"2023","journal-title":"Animal Model. Exp. Med."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"(Impo)Random Forests(Book)","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_33","unstructured":"Lewis, R.J. (2000, January 22\u201325). An Introduction to Classification and Regression Tree (CART) Analysis. Proceedings of the 2000 Annual Meeting of the Society for Academic Emergency Medicine, San Francisco, CA, USA."},{"key":"ref_34","first-page":"2079","article-title":"On Over-Fitting in Model Selection and Subsequent Selection Bias in Performance Evaluation","volume":"11","author":"Cawley","year":"2010","journal-title":"J. Mach. Learn. Res."},{"key":"ref_35","first-page":"56","article-title":"Intestinal Cancer Development in Response to Oral Infection with High-Fat Diet-Induced Type 2 Diabetes (T2D) in Collaborative Cross Mice under Different Host Genetic Background Effects","volume":"34","author":"Lone","year":"2023","journal-title":"Mamm. Genome"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.ajodo.2013.02.019","article-title":"Phenotypic Diversity in White Adults with Moderate to Severe Class III Malocclusion","volume":"144","author":"Uribe","year":"2013","journal-title":"Am. J. Orthod. Dentofac. Orthop."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1093\/ejo\/17.3.231","article-title":"Cluster Analysis Application to Class I Malocclusion","volume":"17","author":"Espona","year":"1995","journal-title":"Eur. J. Orthod."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"511","DOI":"10.1007\/s00784-024-05900-2","article-title":"Lateral Cephalometric Parameters among Arab Skeletal Classes II and III Patients and Applying Machine Learning Models","volume":"28","author":"Midlej","year":"2024","journal-title":"Clin. Oral. Investig."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1007\/978-981-33-4355-9_22","article-title":"Prediction of Malocclusion Pattern of the Orthodontic Patients Using a Classification Model","volume":"Volume 176","author":"Jayathilake","year":"2021","journal-title":"Proceedings of International Conference on Sustainable Expert Systems"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"22","DOI":"10.22531\/muglajsci.1108397","article-title":"Comparative analysis of three machine learning models for early prediction of skeletal Class III malocclusion from profile photos","volume":"8","author":"Aksoy","year":"2022","journal-title":"Mugla J. Sci. Technol."}],"container-title":["Journal of Clinical Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2077-0383\/14\/3\/792\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,8]],"date-time":"2025-10-08T10:36:13Z","timestamp":1759919773000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2077-0383\/14\/3\/792"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,25]]},"references-count":40,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2025,2]]}},"alternative-id":["jcm14030792"],"URL":"https:\/\/doi.org\/10.3390\/jcm14030792","relation":{},"ISSN":["2077-0383"],"issn-type":[{"value":"2077-0383","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1,25]]}}}