Deep Learning-Based Image Classification and Segmentation on Digital Histopathology for Oral Squamous Cell Carcinoma: A Systematic Review and Meta-Analysis.

Background: Artificial intelligence (AI)-based tools have shown promise in histopathology image analysis in improving the accuracy of oral squamous cell carcinoma (OSCC) detection with intent to reduce human error.

Objectives: This systematic review and meta-analysis evaluated deep learning (DL) models for OSCC detection on histopathology images by assessing common diagnostic performance evaluation metrics for AI-based medical image analysis studies.

Methods: Diagnostic accuracy studies that used DL models for the analysis of histopathological images of OSCC compared to the reference standard were analyzed.

A hierarchical deep learning approach for diagnosing impacted canine-induced root resorption via cone-beam computed tomography.

Objectives: Canine-induced root resorption (CIRR) is caused by impacted canines and CBCT images have shown to be more accurate in diagnosing CIRR than panoramic and periapical radiographs with the reported AUCs being 0.95, 0.49, and 0.

Artificial intelligence for classification and detection of oral mucosa lesions on photographs: a systematic review and meta-analysis.

Objective: This study aimed to review and synthesize studies using artificial intelligence (AI) for classifying, detecting, or segmenting oral mucosal lesions on photographs.

Materials And Method: Inclusion criteria were (1) studies employing AI to (2) classify, detect, or segment oral mucosa lesions, (3) on oral photographs of human subjects. Included studies were assessed for risk of bias using Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2).

Effect of mechanical forces on the behavior of osteoblasts: a systematic review of in vitro studies.

Mechanical loading can play a critical role in bone modeling/remodeling through osteoblasts, with several factors being involved in this process.The present study aims to systematically review the effect of mechanical stimulation on human osteoblast cell lineage combined with other variables.The PubMed and Scopus databases were electronically searched for studies analyzing the effect of compression and tension on human osteoblasts at different differentiation stages.

Artificial Intelligence for Detection of External Cervical Resorption Using Label-Efficient Self-Supervised Learning Method.

Introduction: The aim of this study was to leverage label-efficient self-supervised learning (SSL) to train a model that can detect ECR and differentiate it from caries.

Methods: Periapical (PA) radiographs of teeth with ECR defects were collected. Two board-certified endodontists reviewed PA radiographs and cone beam computed tomographic (CBCT) images independently to determine presence of ECR (ground truth).

Deep learning for diagnosis of head and neck cancers through radiographic data: a systematic review and meta-analysis.

Purpose: This study aims to review deep learning applications for detecting head and neck cancer (HNC) using magnetic resonance imaging (MRI) and radiographic data.

Methods: Through January 2023, a PubMed, Scopus, Embase, Google Scholar, IEEE, and arXiv search were carried out. The inclusion criteria were implementing head and neck medical images (computed tomography (CT), positron emission tomography (PET), MRI, Planar scans, and panoramic X-ray) of human subjects with segmentation, object detection, and classification deep learning models for head and neck cancers.

Evaluation of AI Model for Cephalometric Landmark Classification (TG Dental).

The accuracy of cephalometric landmark identification for malocclusion classification is essential for diagnosis and treatment planning. Identifying these landmarks is often complex and time-consuming for orthodontists. An AI model for classification was recently developed.

A deep learning framework to scale linear facial measurements to actual size using horizontal visible iris diameter: a study on an Iranian population.

Digital images allow for the objective evaluation of facial appearance and abnormalities as well as treatment outcomes and stability. With the advancement of technology, manual clinical measurements can be replaced with fully automatic photographic assessments. However, obtaining millimetric measurements on photographs does not provide clinicians with their actual value due to different image magnification ratios.

Comparison of pleasant and unpleasant smile characteristics in the perception of the laypeople in an Iranian population.

Introduction: This study aimed to compare the characteristics of pleasant and unpleasant smiles from the perception of laypeople.

Methods: Two-hundred posed smile photographs were obtained from adult participants with no anomaly, restoration, or severe crowding and spacing in anterior teeth. Photographs were shown to 26 judges to give each photograph a score for attractiveness.

Effects of distraction osteogenesis with Le Fort osteotomies on upper airway volumes: a systematic review and meta-analyses.

Objective: Distraction osteogenesis is one of the treatment options in patients with severe maxillomandibular abnormalities to treat morphological and respiratory problems (obstructive sleep apnea syndrome). The study aimed to evaluate the effect of Le Fort I, II and III distraction osteogenesis (DO) on upper airway dimensions and respiratory function.

Methods: Electronic search was performed in PubMed, Scopus, Embase, Google Scholar and Cochrane databases.

Applications of Machine Learning in Facial Cosmetic Surgeries: A Scoping Review.

Objective: To review the application of machine learning (ML) in the facial cosmetic surgeries and procedures METHODS AND MATERIALS: Electronic search was conducted in PubMed, Scopus, Embase, Web of Science, ArXiv and Cochrane databases for the studies published until August 2022. Studies that reported the application of ML in various fields of facial cosmetic surgeries were included. The studies' risk of bias (ROB) was assessed using the QUADAS-2 tool and NIH tool for before and after studies.

Evaluation of facial profile characteristics of aesthetically pleasing Iranian faces.

Background: The objective of this study was to assess the soft and hard tissue cephalometric indexes of facial profiles perceived as attractive.

Methods: A total of 360 individuals (180 females and 180 males) with well-balanced faces and no history of orthodontic or cosmetic procedures were selected. Twenty-six raters (13 females and 13 males) rated the attractiveness of profile view photographs of the enrolled individuals.

Deep Learning for Detection of Periapical Radiolucent Lesions: A Systematic Review and Meta-analysis of Diagnostic Test Accuracy.

Introduction: The aim of this systematic review and meta-analysis was to investigate the overall accuracy of deep learning models in detecting periapical (PA) radiolucent lesions in dental radiographs, when compared to expert clinicians.

Methods: Electronic databases of Medline (via PubMed), Embase (via Ovid), Scopus, Google Scholar, and arXiv were searched. Quality of eligible studies was assessed by using Quality Assessment and Diagnostic Accuracy Tool-2.

Comparison of Periodontal Ligament Stem Cells with Mesenchymal Stem Cells from Other Sources: A Scoping Systematic Review of and Studies.

Objective: The application of stem cells in regenerative medicine depends on their biological properties. This scoping review aimed to compare the features of periodontal ligament stem cells (PDLSSCs) with stem cells derived from other sources.

Design: An electronic search in PubMed/Medline, Embase, Scopus, Google Scholar and Science Direct was conducted to identify and studies limited to English language.

Preventive Effect of Professional Fluoride Supplements on Enamel Demineralization in Patients Undergoing Fixed Orthodontic Treatment: A Systematic Review and Meta-Analysis.

Objective: The current study aimed to systematically review the randomized clinical trials assessing the preventive effect of professional fluoride interventions on enamel demineralization in patients undergoing fixed orthodontic treatment.

Methods: The electronic search was performed in PubMed and Cochrane library in September 2021. No restriction was set on the publication date.

Deep learning in periodontology and oral implantology: A scoping review.

Deep learning (DL) has been employed for a wide range of tasks in dentistry. We aimed to systematically review studies employing DL for periodontal and implantological purposes. A systematic electronic search was conducted on four databases (Medline via PubMed, Google Scholar, Scopus, and Embase) and a repository (ArXiv) for publications after 2010, without any limitation on language.

Application of chemical factors for acceleration of consolidation phase of the distraction osteogenesis: a scoping review.

Purpose: This study aimed to analyze the effect of injecting chemical factors compared to conventional distraction osteogenesis (DO) treatment on the bone formation of the distracted area of the maxillofacial region in human and animal studies.

Method: Electronic search was done in PubMed, Scopus, Embase, and Cochrane database for studies published until September 2021. The studies' risk of bias (ROB) was assessed using the Cochrane Collaborations and NIH quality assessment tools.

Rapid maxillary expansion supplementary methods: A scoping review of animal studies.

Introduction: Maxillary constriction is a relatively common condition. Various treatment modalities have been proposed for this condition such as rapid maxillary expansion (RME). Although RME can significantly expand the suture in a relatively short period of time, it has a number of drawbacks, mainly a lengthy retention period.

Efficacy of Regenerative Medicine for Alveolar Cleft Reconstruction: A Systematic Review and Meta-analysis.

Objective: The objective of this study is to analyze the efficacy and complications of regenerative medicine compared to autogenous bone graft for alveolar cleft reconstruction.

Method: Electronic search was done through PubMed, Scopus, Embase and Cochrane databases for the studies published until May 2021. No limitations were considered for the type of the included studies.

Evaluation of the association between gingival phenotype and alveolar bone thickness: A systematic review and meta-analysis.

Objective: To conduct a systematic review and meta-analysis of studies that evaluated the association between gingival phenotype (GP) and the underlying alveolar bone thickness (ABT).

Design: An electronic search was performed in PubMed, Embase, Scopus, ProQuest, and Web of Science. The following inclusion criteria were applied: English original studies that compared the ABT in periodontally healthy patients presenting thin versus thick GPs.

Effect of metformin on the behavior of dental pulp stem cells cultured on freeze-dried bone allografts.

Background: Considering the complications associated with autogenous bone grafting, the use of freezedried bone allograft (FDBA) granules may be considered as an alternative treatment plan.

Objectives: The aim of this study was to evaluate the effect of metformin on both the proliferation and osteogenic capability of dental pulp stem cells (DPSCs) cultured on FDBA granules.

Material And Methods: First, a pilot study was conducted only on DPSCs to confirm cellular viability and the osteoinducing effect of 100 μmol/L metformin.

Alveolar bone thickness overlying healthy maxillary and mandibular teeth: A systematic review and meta-analysis.

Objective: To systematically review and meta-analyse the Alveolar Bone Thickness (ABT) overlying healthy teeth. The secondary objective was to review the association of ABT with gender, age, and smoking.

Materials And Methods: The PubMed, Embase, Scopus, ProQuest, Web of Science, and Cochrane Library databases were searched up to July 2020.

Effect of mesenchymal stem cells with platelet-rich plasma carriers on bone formation after rapid maxillary expansion: An Animal Study.

Objective: To evaluate the effect of bone mesenchymal stem cells (BMSCs) with or without platelet-rich plasma (PRP) carriers on sutural new bone formation after rapid palatal expansion (RPE).

Settings And Sample Population: Sixty male Wistar rats were used in this study.

Material And Methods: All samples were subjected to 50cN of palatal expansion force for 7 days followed by 3 weeks of the retention period.

Machine learning and orthodontics, current trends and the future opportunities: A scoping review.

Introduction: In recent years, artificial intelligence (AI) has been applied in various ways in medicine and dentistry. Advancements in AI technology show promising results in the practice of orthodontics. This scoping review aimed to investigate the effectiveness of AI-based models employed in orthodontic landmark detection, diagnosis, and treatment planning.