Background Temporomandibular disorders (TMDs) are disabling conditions with a negative impact on the quality of life. Their diagnosis is a complex and multi-factorial process that should be conducted by experienced professionals, and most TMDs remain often undetected. Increasing the awareness of un-experienced dentists and supporting the early TMD recognition may help reduce this gap. Artificial intelligence (AI) allowing both to process natural language and to manage large knowledge bases could support the diagnostic process. Objective In this work, we present the experience of an AI-based system for supporting non-expert dentists in early TMD recognition. Methods The system was based on commercially available AI services. The prototype development involved a preliminary domain analysis and relevant literature identification, the implementation of the core cognitive computing services, the web interface and preliminary testing. Performance evaluation included a retrospective review of seven available clinical cases, together with the involvement of expert professionals for usability testing. Results The system comprises one module providing possible diagnoses according to a list of symptoms, and a second one represented by a question and answer tool, based on natural language. We found that, even when using commercial services, the training guided by experts is a key factor and that, despite the generally positive feedback, the application's best target is untrained professionals. Conclusion We provided a preliminary proof of concept of the feasibility of implementing an AI-based system aimed to support non-specialists in the early identification of TMDs, possibly allowing a faster and more frequent referral to second-level medical centres. Our results showed that AI is a useful tool to improve TMD detection by facilitating a primary diagnosis.

Artificial intelligence to support early diagnosis of temporomandibular disorders: A preliminary case study

Reda, Bachar
;
Contardo, Luca;Prenassi, Marco;Marceglia, Sara
2023-01-01

Abstract

Background Temporomandibular disorders (TMDs) are disabling conditions with a negative impact on the quality of life. Their diagnosis is a complex and multi-factorial process that should be conducted by experienced professionals, and most TMDs remain often undetected. Increasing the awareness of un-experienced dentists and supporting the early TMD recognition may help reduce this gap. Artificial intelligence (AI) allowing both to process natural language and to manage large knowledge bases could support the diagnostic process. Objective In this work, we present the experience of an AI-based system for supporting non-expert dentists in early TMD recognition. Methods The system was based on commercially available AI services. The prototype development involved a preliminary domain analysis and relevant literature identification, the implementation of the core cognitive computing services, the web interface and preliminary testing. Performance evaluation included a retrospective review of seven available clinical cases, together with the involvement of expert professionals for usability testing. Results The system comprises one module providing possible diagnoses according to a list of symptoms, and a second one represented by a question and answer tool, based on natural language. We found that, even when using commercial services, the training guided by experts is a key factor and that, despite the generally positive feedback, the application's best target is untrained professionals. Conclusion We provided a preliminary proof of concept of the feasibility of implementing an AI-based system aimed to support non-specialists in the early identification of TMDs, possibly allowing a faster and more frequent referral to second-level medical centres. Our results showed that AI is a useful tool to improve TMD detection by facilitating a primary diagnosis.
File in questo prodotto:
File Dimensione Formato  
J of Oral Rehabilitation - 2022 - Reda - Artificial intelligence to support early diagnosis of temporomandibular disorders .pdf

Accesso chiuso

Tipologia: Documento in Versione Editoriale
Licenza: Copyright Editore
Dimensione 5.96 MB
Formato Adobe PDF
5.96 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
J+of+Oral+Rehabilitation+-+2022+-+Reda+-+Artificial+intelligence+to+support+early+diagnosis+of+temporomandibular+disorders+-Post_print.pdf

Open Access dal 27/10/2023

Tipologia: Bozza finale post-referaggio (post-print)
Licenza: Digital Rights Management non definito
Dimensione 6.61 MB
Formato Adobe PDF
6.61 MB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/3038573
Citazioni
  • ???jsp.display-item.citation.pmc??? 2
  • Scopus 5
  • ???jsp.display-item.citation.isi??? 4
social impact