Case-Based Reasoning: An Applied Technique for Designing Intelligent System for the Differential Diagnosis of Oral Diseases; [استدلال مبتنی بر مورد: تکنیک کاربردی در طراحی سیستم هوشمند در تشخیص افتراقی بیماری های دهان Words:] Publisher

Summary: Can AI help in diagnosing oral diseases? A study found that a web-based intelligent system using case-based reasoning can aid dentists in identifying diseases. #OralHealth #AIinDentistry

Safdari R ; Mansourian A ; Tahmasebian S ; Mohammadzadeh N ; Ehtesham H
Source: Journal of Payavard Salamat Published:2026

Abstract

Background and Aim: Artificial intelligence-based systems can facilitate data management and interpretation in various dental specialties and can be used as auxiliary tools in diagnosis and education. Case-based reasoning is a promising artificial intelligence method for implementing decision support systems in medical sciences. In the current research, this technique has been used to design an intelligent system for the differential diagnosis of oral diseases. Materials and Methods: This research is a developmental study and is applied in terms of results. To create a database of cases, patient data was collected by referring to the specialized polyclinic of the Faculty of Dentistry at Tehran University of Medical Sciences and through clinical interviews. The [feature-value] collection was used to display the cases. The weight of the features was determined through a specialized Delphi survey conducted at the national level and as an online study. The determined weights were stored in the case database and used as similarity evaluation parameters. Then, the similarity index was calculated for each case. Results: The intelligent system designed in this research has been developed based on web technologies. Problem-solving in the case-based reasoning method is done in a cycle and includes four main stages: recovery, reuse, review, and maintenance. The input parameters of the system include clinical indicators, paraclinical indicators, historical data, and management data affecting the diagnosis process. The system provides a prioritized list of differential diagnoses of oral diseases across six main axes as output including Ulcerative, vesicular, and bullous lesions, Red and white lesions of the oral mucosa, Pigmented lesions of the oral mucosa, Benign lesions of the oral cavity, Oral cancer, Salivary gland diseases. Conclusion: The development of the system utilizing case-based reasoning techniques and clinical data processing has the potential to assist dentists in achieving differential diagnosis across six main areas of oral diseases. Copyright © 2026 the Authors.