Diulia Pereira Bubna DDS , Pedro Felipe de Jesus Freitas DDS , Aline Xavier Ferraz DDS , Allan Abuabara MSc , Flares Baratto-Filho PhD , Bianca Marques de Mattos de Araujo PhD , Erika Calvano Kuchler PhD , Liliane Roskamp PhD , Angela Graciela Deliga Schroder PhD , Cristiano Miranda de Araujo PhD
{"title":"Dental Trauma Evo – Development of an Artificial Intelligence-powered Chatbot to Support Professional Management of Dental Trauma","authors":"Diulia Pereira Bubna DDS , Pedro Felipe de Jesus Freitas DDS , Aline Xavier Ferraz DDS , Allan Abuabara MSc , Flares Baratto-Filho PhD , Bianca Marques de Mattos de Araujo PhD , Erika Calvano Kuchler PhD , Liliane Roskamp PhD , Angela Graciela Deliga Schroder PhD , Cristiano Miranda de Araujo PhD","doi":"10.1016/j.joen.2025.05.012","DOIUrl":null,"url":null,"abstract":"<div><h3>Introduction</h3><div>Dental trauma is a public health issue that requires proper clinical management to minimize complications. Artificial intelligence-based technologies can support decision-making by providing standardized guidance. This study developed and evaluated an artificial intelligence-powered chatbot to assist professionals in managing dental trauma.</div></div><div><h3>Methods</h3><div>The Dental Trauma Evo chatbot was developed based on the guidelines of the International Association of Dental Traumatology<span>, utilizing a rule-based system to ensure recommendations aligned with established clinical protocols. The chatbot was implemented in Python, integrated with the ChatGPT-4 API, and made available via Streamlit, enabling interactions in over 50 languages. Validation was conducted by specialists in endodontics<span> and pediatric dentistry, who assessed the clarity and consistency of the responses. Performance was evaluated through 384 interactions covering 32 types of trauma, assessing the accuracy and completeness of the recommendations.</span></span></div></div><div><h3>Results</h3><div>The chatbot achieved 100% accuracy in recommending appropriate clinical management. However, some initial responses did not include all treatment options outlined in the guidelines, particularly in cases of enamel, dentin, and pulp-exposed fractures in primary teeth<span>, where only 53% of responses were complete. After adjustments to the code, the second round of testing showed significant improvements, reaching 100% completeness in most cases. Only the recommendations for the reimplantation of avulsed teeth with an open apex reached 93%, indicating the need for further refinements.</span></div></div><div><h3>Conclusions</h3><div>The artificial intelligence-powered chatbot demonstrated high performance in standardizing the management of dental trauma, proving its potential to assist professionals in decision-making by providing quick and precise responses aligned with international guidelines.</div></div>","PeriodicalId":15703,"journal":{"name":"Journal of endodontics","volume":"51 9","pages":"Pages 1229-1234"},"PeriodicalIF":3.6000,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of endodontics","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0099239925002675","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"DENTISTRY, ORAL SURGERY & MEDICINE","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction
Dental trauma is a public health issue that requires proper clinical management to minimize complications. Artificial intelligence-based technologies can support decision-making by providing standardized guidance. This study developed and evaluated an artificial intelligence-powered chatbot to assist professionals in managing dental trauma.
Methods
The Dental Trauma Evo chatbot was developed based on the guidelines of the International Association of Dental Traumatology, utilizing a rule-based system to ensure recommendations aligned with established clinical protocols. The chatbot was implemented in Python, integrated with the ChatGPT-4 API, and made available via Streamlit, enabling interactions in over 50 languages. Validation was conducted by specialists in endodontics and pediatric dentistry, who assessed the clarity and consistency of the responses. Performance was evaluated through 384 interactions covering 32 types of trauma, assessing the accuracy and completeness of the recommendations.
Results
The chatbot achieved 100% accuracy in recommending appropriate clinical management. However, some initial responses did not include all treatment options outlined in the guidelines, particularly in cases of enamel, dentin, and pulp-exposed fractures in primary teeth, where only 53% of responses were complete. After adjustments to the code, the second round of testing showed significant improvements, reaching 100% completeness in most cases. Only the recommendations for the reimplantation of avulsed teeth with an open apex reached 93%, indicating the need for further refinements.
Conclusions
The artificial intelligence-powered chatbot demonstrated high performance in standardizing the management of dental trauma, proving its potential to assist professionals in decision-making by providing quick and precise responses aligned with international guidelines.
期刊介绍:
The Journal of Endodontics, the official journal of the American Association of Endodontists, publishes scientific articles, case reports and comparison studies evaluating materials and methods of pulp conservation and endodontic treatment. Endodontists and general dentists can learn about new concepts in root canal treatment and the latest advances in techniques and instrumentation in the one journal that helps them keep pace with rapid changes in this field.