Case-Based Reasoning to Classify Endodontic Retreatments

Within the field of odontology, an analysis of the probability of success of endodontic retreatment facilitates the diagnostic and decision-making process of medical personnel. This study presents a case-based reasoning system that predicts the probability of success and failure of retreatments to avoid extraction. Different classifiers were applied during the reuse phase of the case-based reasoning process. The system was tested on a set of patients who received retreatments, and a set of variables considered to be of particular interest, were selected

Retreatment Predictions in Odontology by means of CBR Systems

The field of odontology requires an appropriate adjustment of treatments according to the circumstances of each patient. A follow-up treatment for a patient experiencing problems from a previous procedure such as endodontic therapy, for example, may not necessarily preclude the possibility of extraction. It is therefore necessary to investigate new solutions aimed at analyzing data and, with regard to the given values, determine whether dental retreatment is required. In this work, we present a decision support system which applies the case-based reasoning (CBR) paradigm, specifically designed to predict the practicality of performing or not performing a retreatment. Thus, the system uses previous experiences to provide new predictions, which is completely innovative in the field of odontology. The proposed prediction technique includes an innovative combination of methods that minimizes false negatives to the greatest possible extent. False negatives refer to a prediction favoring a retreatment when in fact it would be ineffective. The combination of methods is performed by applying an optimization problem to reduce incorrect classifications and takes into account different parameters, such as precision, recall, and statistical probabilities. The proposed system was tested in a real environment and the results obtained are promising

Retreatment predictions in odontology by means of CBR Systems

The field of odontology requires an appropriate adjustment of treatments according to the circumstances of each patient. A follow-up treatment for a patient experiencing problems from a previous procedure such as endodontic therapy, for example, may not necessarily preclude the possibility of extraction. It is therefore necessary to investigate new solutions aimed at analyzing data and, with regard to the given values, determine whether dental retreatment is required. In this work, we present a decision support system which applies the case-based reasoning (CBR) paradigm, specifically designed to predict the practicality of performing or not performing a retreatment. Thus, the system uses previous experiences to provide new predictions, which is completely innovative in the field of odontology. The proposed prediction technique includes an innovative combination of methods that minimizes false negatives to the greatest possible extent. False negatives refer to a prediction favoring a retreatment when in fact it would be ineffective. The combination of methods is performed by applying an optimization problem to reduce incorrect classifications and takes into account different parameters, such as precision, recall, and statistical probabilities. The proposed system was tested in a real environment and the results obtained are promising

THE DEVELOPMENT OF THE ENDODONTIC COMPLEXITY ASSESSMENT TOOL (E-CAT) FOR ASSESSING ENDODONTIC COMPLEXITY AND ITS PREVALENCE IN GENERAL DENTAL PRACTICE

THE DEVELOPMENT OF THE ENDODONTIC COMPLEXITY ASSESSMENT TOOL (E-CAT) FOR ASSESSING ENDODONTIC COMPLEXITY AND ITS PREVALENCE IN GENERAL DENTAL PRACTICE O. Essam* BDS, E. L. Boyle BSc BDS PhD and F. D. Jarad BDS PhD (Department of Restorative Dentistry, University of Liverpool, United Kingdom) Introduction: The need for endodontic treatment in dental care is a well-established in the literature. A substantial perceived need for referring endodontic cases to endodontic specialists has been reported. In order to improve the success rate for endodontic treatment by general dental practitioners (GDPs), the referral of the more complex cases to an experienced endodontist should be made possible in the best interest of the patient. In order to be able to refer such cases appropriately, two requirements need to be satisfied. Firstly, GDPs need to be able to predictably identify the cases with higher complexity and higher risk of adverse outcomes, then treat or refer to the appropriate practitioner. Secondly, there needs to be a sufficient number of endodontic specialists or endodontic workforce with appropriate referral pathways available. Aims: The aims of this project are therefore twofold. First is to develop a valid and reliable digital assessment tool that can help GDPs assess and classify complex non-surgical root canal treatments (NSRCT). Secondly is to determine the prevalence of endodontic complexity in general dental practice to help assess the level of need for endodontic treatment, training and therefore inform commissioning within the health system. Methodology: The first part of the research focused on the development of the Endodontic Complexity Assessment Tool (E-CAT). This included a review of the current literature, iterative analysis of the complexity factors and the development of digital software to enhance the tool’s efficiency and practicality. Inter-observer and intra-observer reliability studies were conducted with 15 dentists utilising the tool to assess 15 clinical cases and repeating the experiment 9 months later. External validation of the tool was sought with a panel of 35 endodontists to assess the same 15 cases. The consensus of the panel on the complexity of each case was considered as “gold standard” assessment and was compared to the outcome of achieved by the E-CAT. For the prevalence study, 30 fully qualified dentists working within general dental practice across the UK were recruited. Each dentist assessed 10-15 consecutive potential endodontic cases as encountered in their day-to-day clinical practice. The data was collected using the online E-CAT. The tool allowed the data to be recorded into a secure database. Information on tooth-related factors, systemic factors, oral diagnosis and patient-related factors was recorded. Three levels of complexity were defined for the analysis; class I (uncomplicated), class II (moderately complicated) and class III (highly complicated). The data was analysed to express period prevalence with a 95% confidence interval using SPSS statistical software. Results: The E-CAT was successfully developed with a total of 22 complexity criteria; the tool was hosted on a secure university server under the domain of www.e-cat.uk. The inter-user and intra-user reliability was found to be 0.80 and 0.90 respectively. The consensus of the endodontists panel matched to all 15 cases assessed. The inter-examiner correlation of the panel was 0.51. The average time to assess a case was 01:36 minute. A total of 435 endodontic cases were recorded for the prevalence study. The distribution of complexity over classes I, II and III was 39.8%, 31.9% and 28.3% respectively. History of previous root canal intervention formed 22.9% of the cases encountered. The majority of the cases (64.4%) appeared to have 40° curvature. Teeth with existing extra-coronal restorations formed 18.8% of the cases encountered. Radiographically, visible or moderately reduced canal space was reported in 76.9% of the cases, while 20.9% had severely reduced canal space and only 3.2% were perceived to have invisible canal space. History of trauma was encountered in 8.9% of the evaluated cases. Conclusion: The E-CAT provides an efficient and reliable platform to assess the complexity of NSRCT. The results obtained in the prevalence study provide a good resource and databank for researchers, public health commissioners and academic institutions to access wide range of information concerning the prevalence and distribution of endodontic complexity. The results obtained in this research indicate a possible shortage of endodontic specialist service in the UK, especially within the National Health Service