Integrating AI With Cyber Security for Smart Industry 4.0 Application

Longevity Recommendation for Root Canal Treatment Using Machine Learning

“…Patient Information: This factor could include [23] demographic details, such as age, gender, and possibly medical history. Patient characteristics can influence the success or failure of RCT, as some individuals may be more prone to dental issues.…”

“…Following feature extraction and normalization, the data pertaining to root canal therapy were used to train machine learning models like SVM, NB, and LR. The factors of the ideal RCT [21][22][23] or its failures can then be identified by comparing the test data to the training data system. In this scenario, we employed 10-fold cross-validation to ensure that our fitting technique was accurate.…”