Artificial neural network evaluation might help predict postoperative root canal treatment pain
WUHAN, China: Patients frequently suffer from postoperative pain, which is why information about precise medication is urgently needed by dentists today. In a recent study, an artificial neural network (ANN) model was used to predict pain after root canal treatment (RTC), which is of clinical importance for doctors in order to improve the quality of treatment, establish optimised treatment plans and reduce the occurrence of medical disputes.
In the field of nature-inspired algorithms, ANN has had the most recent rapid development. It is a system based on human brain structure and function imitation that can be applied to analyse the relationship between various predictors. ANN can be used to predict medical results by selecting proper neural network structures and training weight and can be used for disease diagnosis, prognosis and clinical decision-making.
It is reported that ANN may make it possible to identify important variables and predict post-treatment pain with high accuracy. This study by researchers from Wuhan University aimed at evaluating the accuracy of the back propagation (BP) artificial neural network model for predicting postoperative pain after RCT.
The BP neural network model was developed using MATLAB 7.0’s neural network toolbox, and a functional projective relationship was established between 13 parameters, (including personal factors, inflammatory reaction factors and operative procedure factors) and the postoperative pain experienced by the patient after RCT.
This neural network model was trained and tested based on data from 300 patients who underwent RCT. Of these cases, 210, 45 and 45 were allocated as the training, data validation and test samples, respectively, to assess the accuracy of prediction. Study authors Xin Gao and Xing Xin and their team found that the accuracy of this BP neural network model was 95.6% for the prediction of postoperative pain after RCT.
The scientists concluded that the BP network model could be used to predict postoperative pain after RCT and showed clinical feasibility and application value. Therefore, the proposed method could be used as a clinical reference in the future.
The study, titled “Predicting postoperative pain following root canal treatment by using artificial neural network evaluation”, was published on 26 August 2021 in Scientific Reports.