This narrative review aims to appraise the evidence on artificial intelligence models for early diagnosis and risk stratification of oral cancer, focusing on data modalities, methodology differences, applications in the diagnostic flow and models’ performance. Models for early diagnosis and screening provide non-invasive diagnosis without the need for specialized instruments, which is ideal for early detection as a low-cost system. Supervised learning with well-annotated data provides reliable references for training the models, and therefore, reliable and promising results. Risk prediction models can be built based on medical record data, demographic data, clinical/histopathological descriptors, highly standardized images or a combination of these. Insights on which patients have a greater chance of malignancy development or disease recurrence can aid in providing personalized care, which can improve the patient’s prognosis. Artificial intelligence models demonstrate promising results in early diagnosis and risk stratification of oral cancer.

Objective: To determine the prevalence and clinical profile of treatment‐related adverse events (TRAE) associated with: (1) botulinum toxin in the upper face; (2) hyaluronic acid fillers in the lower face and nasolabial folds; and (3) nonsurgical facelifts with absorbable threads. Methods: Searches were conducted in five electronic databases and gray literature. Proportion meta‐analyses were performed to estimate the prevalence of TRAE for each type of aesthetic procedure. Results: 42 studies were included. TRAEs were reported in 34.8% of included patients. The highest TRAEs prevalence was associated with hyaluronic acid fillers (63.0%, 95% CI: 35%–84%), followed by nonsurgical facelifts with absorbable threads (20.0%, 95% CI: 8%–41%) and botulinum toxin in the upper face (18.0%, 95% CI: 10%–32%). The most frequently reported TRAEs were swelling (22.4%) and pain (19.0%) for hyaluronic acid fillers; pain (31.5%) and bruising (23.4%) for nonsurgical facelifts with threads; and headache for botulinum toxins. Hyaluronic acid fillers accounted for 67.3% of all TRAEs ( n = 3729/4971). Conclusions: The overall prevalence of adverse events was low for botulinum toxin and thread lifts, but high for hyaluronic acid fillers. Future studies should report all adverse events, expected and not expected, detailing the number of patients affected, total events, onset and recovery times, severity, and provider category.

Objective: Patients with burning mouth syndrome (BMS) suffer from oral pain in the absence of oral lesions. Although less frequently, they may also experience extraoral symptoms that are not readily apparent to clinicians. This study aimed to systematically assess the prevalence of associated extraoral symptoms and comorbid disorders in BMS patients. Methods: Comprehensive searches were performed in five electronic databases (PubMed, Web of Science, Scopus, Embase, and LILACS). Observational studies that reported extraoral symptoms in primary BMS patients were included. The collected data were analyzed descriptively. The quality assessment of the included studies was conducted using the Joanna Briggs Institute tools. Results: We included 22 studies encompassing 2786 BMS patients. Most patients were female ( n = 2138; 76.7%). BMS‐associated extraoral symptoms and comorbidities disorders included sleep disturbances (71.8%), anxiety (65.7%), depression (60.6%), alexithymia (6.1%), tinnitus (5.9%), low back pain (45.3%), and headache (4.4%). Fifteen studies were classified as low risk, six as moderate risk, and one as high risk of bias. Conclusions: BMS patients experience associated extraoral symptoms and comorbid disorders in addition to intraoral pain. These symptoms must be taken into account by clinicians and receive appropriate clinical treatment, as they can significantly affect patients’ quality of life.

Teledentistry has emerged as a promising tool in bridging the gap in healthcare accessibility, particularly in regions like Latin America region, where resources for oral healthcare are often limited. Drawing upon a comprehensive review of literature, this overview assessed the applications and clinical outcomes of teledentistry in diagnosing oral potentially malignant disorders (OPMDs) and oral cancer, highlighting the challenges and opportunities specific to the Latin American context. Moreover, it examined the integration of artificial intelligence algorithms and teledentistry for enhancing diagnostic accuracy, thereby optimizing resource allocation and improving patient outcomes. By elucidating the current landscape and future prospects, this overview provided insights for policymakers, healthcare providers, and researchers, fostering advancements in oral healthcare delivery with the aim of reducing the burden of OPMDs and oral cancer in the Latin American region.