Artificial neural network promising tool in pain prediction after RCT: Study
With the development of endodontic treatment, the incidence of pain and swelling during RCT is only approximately 10%. However, patients frequently report of postoperative pain.
Prospective clinical studies have revealed that approximately 21%, 15% and 7% of patients have mild, moderate and severe pain, respectively, after RCT. The rapid and accurate prediction of postoperative pain is necessary in root canal therapy, which can be conducive to the formulation of follow-up diagnosis and treatment plans, the adoption of preventive measures. To date,practitioners often assess pain after RCT on the basis of personal clinical experience with no universally accepted objective methods.
According to a recent research where researchers used Artificial neural network -ANN model to estimate the post-operative pain of RCT, has highlighted an accuracy as high as 95.60%, which can prove to be of significant clinical value in assessing dental pain post RCT by dentists. The novel research has been put forth in Scientific Reports,a Nature publication.
Artificial neural network (ANN) is the most recent and rapid development in the field of nature-inspired algorithms. ANN is a system based on the human brain structure and function imitation. It may play an important role in providing technical possibilities for predicting pain, as well as understanding of the individual physiological mechanisms of pain and treatment.
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