Results 241 to 250 of about 13,891,192 (336)
ABSTRACT Aim Artificial intelligence (AI) has the potential to aid clinicians in assessing case difficulty in endodontics. The objectives of this study were to develop and validate deep learning models for the detection of clinically negotiable MB2 canals in periapical images of maxillary first and second molars, and to compare the performance of AI ...
Seyed AmirHossein Ourang +8 more
wiley +1 more source
Endodontic Treatment of a Maxillary First Molar With Two Separate Palatal Roots: A Case Report. [PDF]
Liu H, Shen Y.
europepmc +1 more source
Machine Learning Model for Predicting Postoperative Pain in Cases of Irreversible Pulpitis
ABSTRACT Aim Postoperative pain is a frequent clinical concern following endodontic treatment. This study aimed to develop and validate supervised machine learning models to predict the occurrence of postoperative pain in cases of irreversible pulpitis.
Pedro Felipe de Jesus Freitas +9 more
wiley +1 more source
Evaluation of root and root canal morphology in maxillary first molar teeth: A cone-beam computed tomography study using two classification systems in a Japanese population. [PDF]
Watanabe S +3 more
europepmc +1 more source
ABSTRACT Background Computer vision methods based on artificial intelligence (AI) have found numerous applications in endodontic diagnosis and treatment planning. While most current applications employ discriminative deep learning models for detection and classification tasks, the field is now witnessing the rise of generative AI (GenAI), a class of AI
Hossein Mohammad‐Rahimi +6 more
wiley +1 more source
An unusual case of maxillary first molar with seven canals and the successful surgical recovery of a separated instrument. [PDF]
Kadoo S +5 more
europepmc +1 more source
ABSTRACT Aim Apical periodontitis (AP) diagnosis primarily relies on periapical radiographs (PRs) and the Periapical Index (PAI) scoring system. However, existing automated approaches often simplify PAI into binary categories or ignore essential clinical metadata, limiting diagnostic performance and applicability.
Jiyun Lee +3 more
wiley +1 more source

