Designing and evaluation of an intelligent software to diagnosis and present treatment plan for tooth pulp and periapical state

One of the branches of computer science that tries to simulate human intelligence is artificial intelligence. Correct diagnosis of pulp and periapical lesions can prevent various problems and spread of disease. The aim of this study was to use a decision support system (DSS) with a fast and accurate data processing capacity to diagnose and present treatment plan for pulp and periapical lesions in order to have an accurate and rapid access to gold standard results with minimum error.

In the present study on diagnostic research, raw data was collected, revised and approved by professors as the gold standard in order to design the software. Preliminary data was standardized by writing an algorithm and then converted into a flowchart. Next, the programmer started simulation with the Visual C++ Compiler under Windows 7. α and β versions were delivered to professionals in order to fix bugs. Finally, performance evaluation of gold release (final) version was carried out by taking signs of 43 patient samples and transferring them to this version. Statistical analysis of the results was carried out with SPSS 17 at a 95% confidence interval.

The results showed that the overall efficacy of the software was 86.21%; software efficacy scores for periapical diagnosis, treatment plan and periapical diagnosis were 89.66%, 86.21% and 82.76%, respectively.

This software with high data storage and recall details can assist the dental practitioner as a reliable tool in the diagnosis and appropriate endodontic treatment planning.