Results 181 to 190 of about 221,103 (301)

Prevalence of Oral Mucosal Lesions in Finnish Adults—Findings From the Healthy Finland Survey

Gerodontology, EarlyView.
ABSTRACT Objectives Oral mucosal lesions (OMLs) are abnormal findings of the oral mucosa. OMLs can be a localized disease due to trauma or infections, a manifestation of systemic or dermatological disease, or a sign of neoplasia. The aim of this study was to assess the prevalence of OMLs among Finnish adults.
Mirjami J. Rintala, Heidi E. Tuominen, Hanna K. Laine, Anna L. Suominen, Ulla Harjunmaa, Jaana Rautava   +5 more
wiley   +1 more source

Maxillary sinus morphometry and root-sinus proximity in the posterior maxilla: a CBCT study. [PDF]

Saudi Dent J
Madi M.
europepmc   +1 more source

Orofacial pain disorder or trigeminal autonomic cephalalgia? Insights into pathophysiology and implications in medicine and dentistry

Headache: The Journal of Head and Face Pain, EarlyView.
There are some headache disorders known as trigeminal autonomic cephalalgias (TACs). When these “headaches” are localized in the mid‐face region, they are known as “trigeminal autonomic orofacial pains” (TAOPs), and they can mimic other types of face pains including dental pain, which puts the patient at risk of receiving treatments that are incorrect.
Marcela Romero‐Reyes, Simon Akerman
wiley   +1 more source

Removal of a large maxillary sinus mucocele via Le Fort I osteotomy during orthognathic surgery: a case report. [PDF]

J Surg Case Rep
Boylu D, Boylu ÖF.
europepmc   +1 more source

Artificial Intelligence in the Detection of Clinically Negotiable Second Mesio‐Buccal Canals in Periapical Images of Maxillary Molars

International Endodontic Journal, EarlyView.
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, Fatemeh Sohrabniya, Soroush Sadr, Jane Lee, Noreen Ramzy, Alan S. Law, Ernest W. N. Lam, Asma Ahmed Khan, Ali Nosrat   +8 more
wiley   +1 more source

Active learning-assisted deep learning for automated maxillary sinus segmentation in dental cone-beam computed tomography. [PDF]

J Dent Sci
Chen H, Nguyen KD, Chang CL, Doan HT, Chang YC, Porntaveetus T, Hong G, Lo WL, Wang DH, Hsu ML.   +9 more
europepmc   +1 more source

Generative Artificial Intelligence for Computer Vision in Endodontics: A Review of Current State and Future Potential

International Endodontic Journal, EarlyView.
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, Sanyam Jain, Khuram Naveed, Sepanta Hosseinpour, Lise‐Lotte Kirkevang, Ali Nosrat, Ruben Pauwels   +6 more
wiley   +1 more source

Digital 3D-Printed Surgical Guide for Removal of a Separated Instrument at the Maxillary Sinus Floor and Apical Microsurgery. [PDF]

J Med Cases
Li BC, Ye S, Lu CH, Huang G, Xu SM.
europepmc   +1 more source

Deep Learning Models for Detection of Periapical Radiolucent Lesions on Panoramic Radiographs: A Systematic Review and Meta‐Analysis

International Endodontic Journal, EarlyView.
ABSTRACT Background Panoramic radiographs are used routinely to screen dental conditions and treatment patterns. Recently, numerous studies have suggested that deep learning (DL) models can be utilized for analysing panoramic radiographs. Objective This review aimed to evaluate the accuracy of DL models in detecting periapical radiolucent lesions (PRLs)
Ibrahim Ali Ahmad, Raidan Ba‐Hattab, Sadeq Ali Al‐Maweri, Faleh Tamimi   +3 more
wiley   +1 more source

Morphometric Analysis of the Maxillary Sinus Using CT-Based Air-Cavity Reconstruction: A Retrospective Study. [PDF]

J Clin Med
İsmailoğlu P, Bayramoğlu A, Yemiş T, Sadıkzade M, Akbaytürk N, Erdivanlı ÖÇ.   +5 more
europepmc   +1 more source