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The use of artificial intelligence appears to be associated with an increase in the success rate of endodontic treatment outcomes and improvement in the treatment plan.
A comprehensive review demonstrated the diagnostic and prognostic accuracy of a relatively new technology artificial intelligence in the field of endodontic dentistry. Researchers sought to explore the use of artificial intelligence in endodontic dentistry. Using keywords like artificial intelligence, machine learning, deep learning, application, endodontics, and dentistry, the literature published over the last four decades was explored in electronic databases like Scopus, Web of Science, Google Scholar, Embase, PubMed, and Medline.
A total of 2560 articles were found in the preliminary search and 88 articles satisfied the requirements for eligibility. In endodontics, the majority of research on the use of artificial intelligence has focused on tracing the apical foramen, confirming the working length, projecting periapical diseases, root morphologies, retreatment predictions, and identifying vertical root fractures. In terms of prognostic and diagnostic assessments, artificial intelligence demonstrated accuracy in endodontics.
Using artificial intelligence can improve the treatment strategy. This, in turn, can improve the likelihood that endodontic treatment outcomes will be successful. In clinical applications, such as identifying root fractures, periapical diseases, calculating working length, tracing apical foramen, analyzing root morphology, and disease prediction, artificial intelligence is widely employed in endodontics.
Thus, artificial intelligence is rapidly progressing, with promising applications spanning various domains like prognosis, diagnosis, and treatment prediction. But, before incorporating artificial intelligence models into routine clinical work, it is still crucial to carry out additional research to check their expenditure, relevance, and dependability.
Karobari MI
Evaluation of the Diagnostic and Prognostic Accuracy of Artificial Intelligence in Endodontic Dentistry: A Comprehensive Review of Literature
Mohmed Isaqali Karobari et al.
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