[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-123798-en":3,"doc-seo-123798-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},123798,3848291630094,"Emma Wilson","https://eur-avatar.wpscdn.com/davatar_085a072bc5b1113ac321206ff7593b45",8,"Research & Report","A Machine Learning Approach to Evaluating the Relationship between Dental Extraction and Craniofacial Growth in Adolescents - Research Findings and Method","Study purpose: determine whether a relationship exists between orthodontic dental extraction and craniofacial morphological growth patterns in adolescents, and assess it to support medical decision-making. The work applies multiple machine learning methods to a dataset describing orthodontic tooth extraction cases. Results show that simple decision rules can identify treatment need in 98.7% of cases, with remaining cases treated as limited and requiring expert review. The study also details relevant dental, arcade, occlusal, facial, and general factors, plus the analytic techniques used.","A Machine Learning Approach to Evaluating the Relationship between Dental Extraction and Craniofacial Growth in Adolescents  \nGuillermo Hern´andez 1 ,2[0000−0002−7481−5961], Alfonso Gonz´alez-Briones 1 ,2[0000−0002−3444−4393], Jos´e Machado3[0000−0003−4121−6169], Pablo Chamoso 1 ,2[0000−0001−5109−3583], and Paulo Novais3[0000−0002−3549−0754]  \n1 BISITE Research Group, University of Salamanca. Edificio Multiusos I+D+i,  \n37007, Salamanca, Spain  \n{guillehg, alfonsogb, [chamoso](chamoso}@usal.es)[}](chamoso}@usal.es)[@usal.es](chamoso}@usal.es)  \n2 Air Institute, IoT Digital Innovation Hub, Carbajosa de la Sagrada, 37188 .  \nSalamanca, Spain  \n3 Algoritmi Center/LASI, University of Minho, 4710-057 Braga, Portugal  \n{jmac, [pjon](pjon}@di.uminho.pt)[}](pjon}@di.uminho.pt)[@di.uminho.pt](pjon}@di.uminho.pt)  \nAbstract. There may be multiple reasons for tooth extraction, such as deep cavities, an infection that has destroyed an important portion of the tooth or the bone that surrounds it, or for orthodontic reasons, such as the lack of space for all the teeth in the mouth. In the case of orthodontics, however, there is a relationship between tooth extraction and the craniofacial morphological pattern. The purpose of this study is to establish whether such a relationship exists in adolescents and to evaluate it and to serve as a tool to support medical decision making..  \nMachine Learning techniques can now be applied to datasets to discover relationships between different variables. Thus, this study involves the application of a series of Machine Learning techniques to a dataset containing information on orthodontic tooth extraction in adolescents. It has been discovered that by following simple rules it is possible to identify the need of treatment in 98.7% of the cases, while the remaining can be regarded as “limited cases”, in which an expert’s opinion is necessary.  \nKeywords: Machine Learning · Craniofacial Morphological Growth · Dental Extraction · Orthodontic treatments.  \n1 Introduction  \nTo successfully complete orthodontic treatment, tooth extraction may sometimes be necessary. The main reasons for this procedure are: to solve negative osteodental discrepancy (severe dental crowding), camouflage a horizontal skeletal discrepancy (class III or class II) or vertical discrepancy (vertical growth pattern or skeletal open bite), to improve the facial aesthetics of the patient in cases of protrusion or lip incompetence, etc. [7] . The present study determines whether tooth extraction is necessary by examining the craniofacial morphology  \n2 G. Hern´andez et al.  \nand the growth pattern. Orthodontists consider different factors when identifying negative osteodental discrepancy. Thus, the rules identified in this paper could support orthodontists’ in making decisions. The following factors have been identified:  \n– Tooth factors: the size of the teeth (macrodontia), number of teeth (supernumerary), pathology (tooth decay, periodontal disease), abnormal position (ectopias, the inclination of the incisors) .  \n– Arcade factors: narrow arcade, osteodental severe discrepancy, changes in the midline.  \n– Occlusal factors: open bite, molar, and canine class, increased overjet.  \n– Facial factors: aesthetics protrusive facial profile and vertical growth patterns.  \n– General factors: patient low growth potential and low degree of patient cooperation.  \nThe presence of crowded and irregular anterior teeth is the most cited reason for seeking orthodontic treatment [25] . Crowding has been associated with vertical growth, lower incisor eruption, and increased vertical dentoalveolar eruption. One might expect crowding and facial divergence to be associated because divergence increases anterior vertical dentoalveolar eruption. Hyperdivergence results in the retroclination of the incisors, which may cause crowding by reducing the arch length.  \nThe following techniques have been employed in this research for data analysis: statistical techniq","cbCaihzCqJ8grUle","https://ap.wps.com/l/cbCaihzCqJ8grUle","pdf",523310,1,14,"English","en",105,"# Introduction\n## Tooth extraction purposes in orthodontics\n## Identified decision factors\n## Data analysis techniques used\n# Biological Background\n## Patient cohort and study setting\n## Craniofacial growth patterns\n# Proposed Analysis Process\n## Variables and identifiers used in the dataset\n# Results and Conclusions","[{\"question\":\"What goal does the study pursue regarding dental extraction and craniofacial growth?\",\"answer\":\"The study establishes whether a relationship exists between orthodontic tooth extraction and craniofacial morphological patterns in adolescents, and evaluates it as a decision-support tool for medical decisions.\"},{\"question\":\"How is the machine learning model used to support orthodontic treatment decisions?\",\"answer\":\"Machine learning techniques are applied to a dataset containing information on orthodontic tooth extraction. The study reports that simple rules can identify treatment need for 98.7% of cases, while the rest are limited and need expert input.\"},{\"question\":\"What factors are considered when determining the need for tooth extraction?\",\"answer\":\"The paper lists tooth factors, arcade factors, occlusal factors, facial factors, and general factors, such as tooth size/pathology, dental crowding patterns, bite characteristics (e.g., open bite, overjet), facial aesthetics and growth patterns, and patient cooperation/low growth potential.\"}]","A Machine Learning Approach to Evaluating the Relationship between Dental Extraction and Craniofacial Growth in Adolescents - Research Findings and Method | PDF",1785818616,35,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"a-machine-learning-approach-to-evaluating-the-relationship-between-dental-extraction-and-craniofacial-growth-in-adolescents-research-findings-and-method","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/a-machine-learning-approach-to-evaluating-the-relationship-between-dental-extraction-and-craniofacial-growth-in-adolescents-research-findings-and-method/123798/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What goal does the study pursue regarding dental extraction and craniofacial growth?","Question",{"text":75,"@type":76},"The study establishes whether a relationship exists between orthodontic tooth extraction and craniofacial morphological patterns in adolescents, and evaluates it as a decision-support tool for medical decisions.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How is the machine learning model used to support orthodontic treatment decisions?",{"text":80,"@type":76},"Machine learning techniques are applied to a dataset containing information on orthodontic tooth extraction. The study reports that simple rules can identify treatment need for 98.7% of cases, while the rest are limited and need expert input.",{"name":82,"@type":73,"acceptedAnswer":83},"What factors are considered when determining the need for tooth extraction?",{"text":84,"@type":76},"The paper lists tooth factors, arcade factors, occlusal factors, facial factors, and general factors, such as tooth size/pathology, dental crowding patterns, bite characteristics (e.g., open bite, overjet), facial aesthetics and growth patterns, and patient cooperation/low growth potential.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]