Orthodontic treatment planning software

Noroozi, Hassan

doi:10.1016/j.ajodo.2006.02.025

Cited by 16 publications

(9 citation statements)

References 9 publications

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“…Noroozi, (2006), (26) Orthodontic treatment planning software The computer program can propose treatment for some special cases, such as incomplete dentition.…”

Section: Diagnosis Of Dental Deformities In Cephalometry Images Usingmentioning

confidence: 99%

“…In three studies, deep convolutional neural network systems were used for orthodontic diagnosis. Six of these 26 articles described orthodontic diagnosis and treatment outcomes using AI and super vector regression [21][22][23][24][25][26]. Sterilization of the models was provided by a touchless sterile method in 1 study [27].…”

Section: Diagnosis Of Dental Deformities In Cephalometry Images Usingmentioning

confidence: 99%

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Artificial intelligence and machine learning in orthodontics

Büyük

Hatal

2019

Ortadogu Tıp Derg

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Objective:The clinical use of information technology in orthodontics has increased significantly in recent years. The aim of this systematic review is to perform a scientific analysis of artificial intelligence and machine learning in orthodontics. Methods:An electronic search and manual search were performed on September 25, 2018 about using artificial intelligence and machine learning in orthodontics. Results:A total of 107 studies were found. Nine studies were excluded because of duplication. After exclusion of all the irrelevant and non-English articles, 23 full-text articles remained to be included in this systematic review. 3 additional articles were included in this systematic review. Twelve automatic cephalometric landmark determination, 6 orthodontic diagnosis and treatment outcomes, 2 orthodontic tooth extraction decision, 3 facial attractiveness, 1 headgear selection, 1 touchless sterilisation system and 1 automatic skeletal age determination studies were included in this systematic review. Conclusions:Artificial intelligence and machine learning are mainly focused on determination of automatic cephalometric points, facial attractiveness and tooth extraction decisions for orthodontic purposes. The use of artificial intelligence in orthodontics is important in terms of obtaining more accurate and rapid results clinically.

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“…Noroozi, (2006), (26) Orthodontic treatment planning software The computer program can propose treatment for some special cases, such as incomplete dentition.…”

Section: Diagnosis Of Dental Deformities In Cephalometry Images Usingmentioning

confidence: 99%

Section: Diagnosis Of Dental Deformities In Cephalometry Images Usingmentioning

confidence: 99%

Artificial intelligence and machine learning in orthodontics

Büyük

Hatal

2019

Ortadogu Tıp Derg

View full text Add to dashboard Cite

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“…Noroozi, hem grafik hem de say›sal formlardaki hasta verilerini iflleyebilen ve sonra hem cerrahi olmayan ortodontik hastalar›n hem de tamamlanmam›fl difllenme gibi baz› özel vakalar için tedavi planlamar› önerebilen yeni bir yaz›l›m tan›mlam›flt›r (26,27). Bulan›k mant›k konsepti, yaz›l›m›n nominal parametreler ile çal›flmas›n› olanakl› k›lm›flt›r.…”

Section: Turkish Journal Of Orthodontics 2007;20:265-272unclassified

“…Noroozi described a new software that can process patient data in both graphic and numeric forms and then propose a treatment plan for nonsurgical orthodontic patients as well as for some special cases, such as incomplete dentition (26,27). The concepts of fuzzy logic enabled the software to work with nominal parameters.…”

Section: Turkish Journal Of Orthodontics 2007;20:265-272mentioning

confidence: 99%

Ortodontik Uzman Sistemler

Akçam¹

2007

Turkish Journal of Orthodontics

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“…The fuzzy logic was applied in orthodontics to select types of headgears 3 , to evaluate the visual subjective judgment of the anteroposterior relationship between maxilla and mandible 4,5 and to establish non-surgical treatment plans. 6 However, a mathematical model based upon fuzzy and paraconsistent logic in order to contextualized cephalometric data has not been presented.…”

Section: Introductionmentioning

confidence: 99%

Diagnóstico cefalométrico eletrônico: contextualização de variáveis cefalométricas

Santo¹,

Santo

2011

Dental Press J. Orthod.

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INTRODUÇÃO: avaliações paramétricas clássicas e variáveis cefalométricas isoladas podem não prover a melhor informação em morfologia craniofacial. Por outro lado, uma cefalometria contextualizada pode ser bem mais promissora, uma vez que permite a integração de variáveis cefalométricas ponderadas. OBJETIVO: a proposta principal desse artigo é apresentar a aplicação de um modelo matemático não-trivial em cefalometria, permitindo a mineração de dados através da filtragem de certeza e contradição em cada "nó" da rede. MÉTODOS: nessa "rede neural" proposta, cada "célula" é conectada a outras "células" através de "sinapses". Tal sistema de tomada de decisão é uma ferramenta de inteligência artificial ajustada para potencialmente aumentar o significado dos dados coletados. RESULTADOS: a comparação entre o diagnóstico final fornecido pela rede neural paraconsistente e as opiniões de três examinadores foi heterogênea. O índice de concordância Kappa foi regular para discrepâncias anteroposteriores; substancial ou regular para discrepâncias verticais; e moderado para discrepâncias dentárias. Para a protrusão bimaxilar dentária, a concordância foi quase perfeita. Similarmente, a concordância entre as opiniões dos três examinadores sem a ajuda de nenhuma ferramenta de diagnóstico foi apenas moderada para discrepâncias esqueletais e dentárias. Como exceção, a concordância para protrusão dentária foi quase perfeita. CONCLUSÕES: a avaliação de desempenho do sistema tecnológico desenvolvido suporta que a ferramenta eletrônica apresentada pode se igualar às decisões humanas na maioria das situações. Como uma limitação esperada, tal ferramenta matemática-computacional se apresentou menos efetiva para discrepâncias esqueletais do que para discrepâncias dentárias.

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Orthodontic treatment planning software

Cited by 16 publications

References 9 publications

Artificial intelligence and machine learning in orthodontics

Artificial intelligence and machine learning in orthodontics

Ortodontik Uzman Sistemler

Diagnóstico cefalométrico eletrônico: contextualização de variáveis cefalométricas

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