Clinical decision support model for tooth extraction therapy derived from electronic dental records

Cui, Qiwen; Chen, Qingxiao; Liu, Pufan; Liu, Debin; Wen, Zaiwen

doi:10.1016/j.prosdent.2020.04.010

Cited by 25 publications

(42 citation statements)

References 29 publications

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“…The included studies were ranged from the year 2000 to 2020. The studies were from four categories: cohort study [5,16,27], case control [28,29], clinical trials [6-12, 17, [30][31][32][33][34][35][36][37][38][39][40][41][42][43], and experimental trials [13-15, 44, 45]. The followup period was mentioned in one study [43].…”

Section: General Characteristics Of Included Studiesmentioning

confidence: 99%

“…According to the standards described in the Cochrane Handbook for Systematic Reviews of Interventions (v5.1.0) [19], the following findings were recorded. Out of the 32 studies [5][6][7][8][9][10][11][12][13][14][15][16][17][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44][45] assessed, 1 study employed blinding [6]. In 5 studies, randomizations [5,7,34,37,39] were performed.…”

Section: Author and Year Reason Of Exclusionmentioning

confidence: 99%

See 1 more Smart Citation

Artificial Intelligence Techniques: Analysis, Application, and Outcome in Dentistry—A Systematic Review

Ahmed

Abbasi

Zuberi

et al. 2021

BioMed Research International

122

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Objective. The objective of this systematic review was to investigate the quality and outcome of studies into artificial intelligence techniques, analysis, and effect in dentistry. Materials and Methods. Using the MeSH keywords: artificial intelligence (AI), dentistry, AI in dentistry, neural networks and dentistry, machine learning, AI dental imaging, and AI treatment recommendations and dentistry. Two investigators performed an electronic search in 5 databases: PubMed/MEDLINE (National Library of Medicine), Scopus (Elsevier), ScienceDirect databases (Elsevier), Web of Science (Clarivate Analytics), and the Cochrane Collaboration (Wiley). The English language articles reporting on AI in different dental specialties were screened for eligibility. Thirty-two full-text articles were selected and systematically analyzed according to a predefined inclusion criterion. These articles were analyzed as per a specific research question, and the relevant data based on article general characteristics, study and control groups, assessment methods, outcomes, and quality assessment were extracted. Results. The initial search identified 175 articles related to AI in dentistry based on the title and abstracts. The full text of 38 articles was assessed for eligibility to exclude studies not fulfilling the inclusion criteria. Six articles not related to AI in dentistry were excluded. Thirty-two articles were included in the systematic review. It was revealed that AI provides accurate patient management, dental diagnosis, prediction, and decision making. Artificial intelligence appeared as a reliable modality to enhance future implications in the various fields of dentistry, i.e., diagnostic dentistry, patient management, head and neck cancer, restorative dentistry, prosthetic dental sciences, orthodontics, radiology, and periodontics. Conclusion. The included studies describe that AI is a reliable tool to make dental care smooth, better, time-saving, and economical for practitioners. AI benefits them in fulfilling patient demand and expectations. The dentists can use AI to ensure quality treatment, better oral health care outcome, and achieve precision. AI can help to predict failures in clinical scenarios and depict reliable solutions. However, AI is increasing the scope of state-of-the-art models in dentistry but is still under development. Further studies are required to assess the clinical performance of AI techniques in dentistry.

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Section: General Characteristics Of Included Studiesmentioning

confidence: 99%

Section: Author and Year Reason Of Exclusionmentioning

confidence: 99%

Artificial Intelligence Techniques: Analysis, Application, and Outcome in Dentistry—A Systematic Review

Ahmed

Abbasi

Zuberi

et al. 2021

BioMed Research International

122

View full text Add to dashboard Cite

show abstract

“…However, a dentist considers not only biological factors but also behavioural, financial and personal risk factors in determining the prognosis of a tooth. 38 A future ML model should incorporate these additional prognostic factors.…”

Section: Prosthodonticsmentioning

confidence: 99%

“…A decision tree algorithm trained from 3559 patient electronic dental records (EDR) has outperformed two prosthodontics in predicting whether a tooth is to be extracted or retained or to undergo endodontic and/or restorative treatment 37 . The model was more conservative than the prosthodontists as shown by a relatively higher recall score.…”

Section: Machine Learningmentioning

confidence: 99%

Promises and perils of artificial intelligence in dentistry

Pethani

2021

Australian Dental Journal

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Artificial intelligence (AI) is a subdiscipline of computer science that has made substantial progress in medicine and there is a growing body of AI research in dentistry. Dentists should have an understanding of the foundational concepts and the ability to critically evaluate dental research in AI. Machine learning (ML) is a subfield of AI that most dental AI research is dedicated to. The most prolific area of ML research is automated interpretation of dental imaging. Other areas include providing treatment recommendations, predicting future disease and treatment outcomes. The research impact is limited by small datasets that do not harness the positive correlation between very large datasets and ML performance. There is also a need to standardize research methodologies and utilize performance metrics that are appropriate for the clinical context. In addition to research challenges, this article discusses the ethical, legal and logistical considerations associated with implementation in clinical practice. This includes explainable AI, model bias, data privacy and security. The future implications of AI in dentistry involve a promise for a novel form of practicing dentistry however, the effect of AI on patient outcomes is yet to be determined.

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“…Cirugía oral. Dentro del área de cirugía Bucomaxiolofacial se ha reportado la utilización de la IA en sus diferentes tipos, entre los que resalta la CNN utilizada tanto en radiografías panorámicas como en TCV para la correcta toma de decisiones de la extracción de un diente, mostrando así la CNN un alto rendimiento en la toma de decisiones 47 . Así mismo, se ha reportado el uso de la red neuronal profunda (DNN) en la localización del conducto dentario inferior, sabiendo que la lesión de este nervio es una de las complicaciones más frecuentes en la extracción de terceras molares inferiores, ya que podría generar parestesia 48 .…”

Section: Revisión Y Discusiónunclassified

Aplicación de la inteligencia artificial en Odontología

Cacñahuaray-Martínez

Gómez-Meza

Lamas-Lara

et al. 2021

Odontol Sanmarquina

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En este artículo se revisó sobre inteligencia artificial (IA) y su aplicación en el campo odontológico. El objetivo fue revisar la evidencia sobre inteligencia artificial y su aplicación en las diferentes especialidades odontológicas. Se realizó una búsqueda en las bases de datos de Medline/PubMed, Scopus y Web of Science desde el año 2017 al 2021. Se encontraron 321 artículos, de los cuales se seleccionaron 62, que mostraron la aplicación de la IA en seis especialidades: periodoncia, implantología, odontología forense, medicina y patología oral, ortodoncia y diagnóstico/cariología/endodoncia. Se encontró que la especialidad con más artículos sobre el tópico de IA fue la de diagnóstico/cariología/endodoncia y el tipo de inteligencia artificial que más se utilizó fue el de red neural convolucional. Se concluyó que la IA se está utilizando ampliamente en odontología demostrando resultados prometedores ya que muestran una precisión equivalente a la de diferentes especialistas capacitados y en algunos casos superan los errores humanos demostrando excelentes resultados.

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Clinical decision support model for tooth extraction therapy derived from electronic dental records

Cited by 25 publications

References 29 publications

Artificial Intelligence Techniques: Analysis, Application, and Outcome in Dentistry—A Systematic Review

Artificial Intelligence Techniques: Analysis, Application, and Outcome in Dentistry—A Systematic Review

Promises and perils of artificial intelligence in dentistry

Aplicación de la inteligencia artificial en Odontología

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