Artificial Intelligence in Periodontology: A Systematic Review
AI shows promise across periodontology, with deep learning achieving strong performance for image‐based diagnosis of periodontitis. However, limited data diversity, inconsistent metrics, and scarce external validation raise concerns about generalizability and clinical applicability.
Antonin Tichy +7 more
wiley +1 more source
An interdisciplinary approach for the management of periapical lesion using regenerative approach: a case report. [PDF]
Jaiswal P +4 more
europepmc +1 more source
Root canal treatment of a six-canal first mandibular molar with extensive periapical lesion: A case report. [PDF]
Li X, Sun S, Zheng T.
europepmc +1 more source
Peri‐Implantitis and Periodontitis: Biological Convergence, Contextual Divergence
Periodontal and peri‐implant tissues differ and coincide in many aspects, from the clinical and radiological perspective, including histology, microbiology, and molecular markers. Thus, health and disease may also follow different and similar routes.
Pablo Galindo‐Moreno +6 more
wiley +1 more source
Nonsurgical Endodontic Retreatment of a Large Cyst-Like Periapical Lesion With Buccal and Palatal Cortical Plate Perforations and Maxillary Sinus Involvement: A 2-Year CBCT Follow-Up Case Report. [PDF]
Elsayed MA, Nawar NN, Karobari MI.
europepmc +1 more source
Platelet‐Rich Fibrins as Local Drug‐Delivery Carriers
Autologous platelet concentrates (APCs), particularly platelet‐rich fibrin (PRF), act as biologically active fibrin scaffolds, capable of entrapping and gradually releasing therapeutic agents in oral and periodontal therapy. The incorporation of bioactive compounds, such as antibiotics, antifungals, vitamins, antidiabetic drugs, and exosomes, enhances ...
Karim M. Fawzy El‐Sayed +1 more
wiley +1 more source
M1 and M2 macrophages markers are alternately expressed during periapical lesion development. [PDF]
Pucinelli CM +8 more
europepmc +1 more source
Management of periapical lesion with persistent exsudate. [PDF]
Quaresma SA +7 more
europepmc +1 more source
ABSTRACT Objectives To develop a deep learning‐based framework to automate sector classification of unerupted maxillary canines (UMCs), assessing its accuracy and reliability compared to human ones. Material and Methods One thousand five hundred twenty‐eight UMCs from digital panoramic radiographs (PRs) were selected using data from the Dental ...
Marzio Galdi +7 more
wiley +1 more source
Deep Learning-Based Periapical Lesion Detection on Panoramic Radiographs. [PDF]
Szabó V +7 more
europepmc +1 more source

