Advancements in artificial intelligence (AI) are poised to catalyze a transformative shift across diverse dental disciplines including endodontics, oral radiology, orthodontics, pediatric dentistry, periodontology, prosthodontics, and restorative dentistry. This narrative review delineates the burgeoning role of AI in enhancing diagnostic precision, streamlining treatment planning, and potentially unveiling innovative therapeutic modalities, thereby elevating patient care standards. Recent analyses corroborate the superiority of AI-assisted methodologies over conventional techniques, affirming their capacity for personalization, accuracy, and efficiency in dental care. Central to these AI applications are convolutional neural networks and deep learning models, which have demonstrated efficacy in diagnosis, prognosis, and therapeutic decision making, in some instances surpassing traditional methods in complex cases. Despite these advancements, the integration of AI into clinical practice is accompanied by challenges, such as data security concerns, the demand for transparency in AI-generated outcomes, and the imperative for ongoing validation to establish the reliability and applicability of AI tools. This review underscores the prospective benefits of AI in dental practice, envisioning AI not as a replacement for dental professionals but as an adjunctive tool that fortifies the dental profession. While AI heralds improvements in diagnostics, treatment planning, and personalized care, ethical and practical considerations must be meticulously navigated to ensure responsible development of AI in dentistry.

Cancer remains a significant global health concern, with increasing genetic and metabolic irregularities linked to its onset. Among various forms of cancer, skin cancer, including squamous cell carcinoma, basal cell carcinoma, and melanoma, is on the rise worldwide, often triggered by ultraviolet (UV) radiation. The propensity of skin cancer to metastasize highlights the importance of early detection for successful treatment. This narrative review explores the evolving role of artificial intelligence (AI) in diagnosing head and neck skin cancers from both radiological and pathological perspectives. In the past two decades, AI has made remarkable progress in skin cancer research, driven by advances in computational capabilities, digitalization of medical images, and radiomics data. AI has shown significant promise in image-based diagnosis across various medical domains. In dermatology, AI has played a pivotal role in refining diagnostic and treatment strategies, including genomic risk assessment. This technology offers substantial potential to aid primary clinicians in improving patient outcomes. Studies have demonstrated AI’s effectiveness in identifying skin lesions, categorizing them, and assessing their malignancy, contributing to earlier interventions and better prognosis. The rising incidence and mortality rates of skin cancer, coupled with the high cost of treatment, emphasize the need for early diagnosis. Further research and integration of AI into clinical practice are warranted to maximize its benefits in skin cancer diagnosis and treatment.

Introduction: Due to the silent manifestation of temporomandibular joint (TMJ), dentists and rheumatologists may neglect treatment for this joint. Aims: The aim of this study was to investigate the TMJ components in patients with various rheumatic diseases and to compare them with a control group based on cone beam computed tomography (CBCT) images. Materials and Methods: This study comprised an assessment of the CBCT images of 65 patients (130 temporomandibular joints) with various rheumatic diseases (mostly rheumatoid arthritis) affecting the TMJ. Moreover, 65 patients (130 temporomandibular joints) with a similar age and gender distribution were examined as the control group. Pathologies were classified into a total of 12 types for the presence of any osseous changes in the condylar head or articular fossa or for joint space narrowing. Statistical analysis of all data was performed with SPSS version 18. The conformity of continuous variables to a normal distribution was examined by the Kolmogorov–Smirnov test. The Mann–Whitney U test was used to compare the means of two independent groups. The Pearson Chi-square test, Yates correction and Fisher’s exact test were used in the analysis of categorical variables. Results: The mean age of the patient and control groups was 50 ± 13 and 48 ± 16, respectively, and no statistically significant difference was found between the patient and control groups in terms of age distribution (p = 0.123). Condylar erosion, condylar flattening, subcondylar sclerosis, osteophytes, subcortical cysts, articular eminence resorption and articular eminence flattening rates were found to be statistically significantly higher in the patient group than in the control group (p < 0.05). Conclusions: Dentomaxillofacial radiologists should examine the bony components of the TMJ in patients with rheumatic diseases, and a multidisciplinary approach involving a dental specialist and rheumatologist is required.

The objective of this study is to explore the prevalence, size, location and radiographic features of osteomas in the paranasal sinuses using cone beam computed tomography imaging. This study was planned as retrospective cross-sectional. 499 consecutive cone beam computed tomography scans obtained in a dentomaxillofacial radiology department for various dental indications. Statistical analysis of all data was done with SPSS version 22. Descriptive statistics and chi-square tests were used to determine the prevalence of categorical parameters. Osteoma was detected in 7 % (n = 35) of the 499 images analyzed. The age of the patients ranged from 6 to 96 years (mean 42.03 ± 18.70). No significant difference was found between the genders (p = 0.77). In terms of localization, it was significantly more common in the ethmoid sinuses (p < 0.01). Cortical type osteoma was observed the most frequently in the analyzed images (p < 0.01). The incidence of osteoma was not significant depending on age (p = 0.50). Osteomas in the paranasal sinuses show a 7 % prevalence in CBCT images, with the ethmoid sinus being the most common site. The average size of osteomas was 3.43 ± 1.78 mm, predominantly cortical in type. These findings highlight the necessity for thorough examination of CBCT images by dentomaxillofacial radiologists to avoid overlooking osteomas.

Fanconi anemia (FA) is a rare autosomal recessive inherited syndrome characterized by chromosomal instability, aplastic anemia and cancer predisposition, accompanied by congenital anomalies. In these patients, the probability of tumor development in the head and neck region is higher than in the normal population. A patient with fanconi aplastic anemia was admitted to our clinic due to painful lesions in the oral cavity. A brush biopsy was taken from the relevant lesions and sent for histopathological examination. No atypical cells were found in the biopsy result, and the patient was called for regular dental check-ups due to the increased risk of malignancy. In this case report, it is aimed to examine the findings of a patient with FA and the necessity of monitoring the intraoral lesions in terms of malignancy risk, in the light of the literature.

Temporomandibular joint (TMJ) disorders are complex and can significantly impact quality of life due to their role in mastication, speech, and facial expressions. Rheumatic diseases such as rheumatoid arthritis, psoriatic arthritis, and systemic lupus erythematosus frequently involve the TMJ, complicating diagnosis and management. Conventional imaging techniques like magnetic resonance imaging (MRI) and computed tomography (CT), while effective, are limited by high costs, accessibility issues, and, in the case of CT, radiation exposure. Ultrasonography emerges as a cost-effective, non-invasive alternative that provides real-time images of both soft and hard tissue structures, enhancing diagnostic accuracy and patient management. This narrative review synthesizes current knowledge and recent advancements in ultrasonic imaging, comparing its efficacy with conventional methods and discussing its potential in guiding therapeutic strategies. The ability of ultrasonography to visualize dynamic changes and detect early signs of involvement makes it particularly valuable in managing chronic rheumatic conditions. However, the technique's effectiveness depends on the operator's expertise, and there is a need for standardized protocols. This review also underscores the importance of a multidisciplinary approach in the diagnosis and management of TMJ disorders in rheumatic disease patients and suggests directions for future research and clinical practice improvements. The integration of high-resolution ultrasonography could revolutionize the diagnostic landscape, offering a patient-friendly, accurate, and accessible tool for the early detection and ongoing monitoring of TMJ disorders.