Background: The rapid adoption of artificial intelligence (AI) models in the medical field is due to their ability to collaborate with clinicians in the diagnosis and management of a wide range of conditions. This research assesses the diagnostic accuracy and therapeutic strategies of Chat Generative Pre-trained Transformer (ChatGPT) in comparison to dental professionals across 12 clinical cases. Methodology: ChatGPT 3.5 was queried for diagnoses and management plans for 12 retrospective cases. Physicians were tasked with rating the complexity of clinical scenarios and their agreement with the ChatGPT responses using a five-point Likert scale. Comparisons were made between the complexity of the cases and the accuracy of the diagnoses and treatment plans. Results: ChatGPT exhibited high accuracy in providing differential diagnoses and acceptable treatment plans. In a survey involving 30 attending physicians, scenarios were rated with an overall median difficulty level of 3, showing acceptable agreement with ChatGPT's differential diagnosis accuracy (overall median 4). Our study revealed lower diagnosis scores correlating with decreased treatment management scores, as demonstrated by univariate ordinal regression analysis. Conclusions: ChatGPT's rapid processing aids healthcare by offering an objective, evidence-based approach, reducing human error and workload. However, potential biases may affect outcomes and challenge less-experienced practitioners. AI in healthcare, including ChatGPT, is still evolving, and further research is needed to understand its full potential in analyzing clinical information, establishing diagnoses, and suggesting treatments.

Jaw cysts are frequent radiolucent lesions in dentistry that can present diagnostic difficulties due to their similar radiographic appearance. This study aimed to develop an AI-based detection and classification system for jaw cysts using the YOLO v11 deep learning model on panoramic radiographs. A total of 311 panoramic images (211 cystic, 100 normal) were labeled and augmented. The YOLO v11 Small model was trained in both multi-class (distinguishing between dentigerous cysts [DCs], odontogenic keratocysts [OKCs], and radicular cysts [RCs]) and single-class configurations (detecting cysts without type differentiation). Performance metrics included precision, recall, F1 score, and mean average precision (mAP). In the multi-class model, the system achieved an mAP of 86%, with precision of 84%, recall of 82%, and F1 score of 83%. Class-wise mean accuracies were 91% for DCs, 85% for OKCs, and 82% for RCs. The single-class model showed slightly lower performance with an mAP of 84% and F1 score of 81%. YOLO v11 demonstrated high accuracy in detecting jaw cysts, indicating its potential to support dental diagnostics. Further validation on larger and balanced datasets is recommended to enhance generalizability.

Background: This study aims to conduct a bibliometric analysis of the current literature related to facial feminization surgery (FFS) and facial masculinization surgery (FMS) to understand the patterns, trends, and evolution of research topics. In addition, it aims to objectively identify the important articles that constitute the primary backbone of the FFS/FMS literature and provide a resource for education and new studies in this emerging field. Results: Using the principles of the Leiden Manifesto, 384 publications from the Web of Science from 1987 to 2023 were analyzed. The analysis included cross-country collaboration, keyword trends, affiliations, co-citation networks, and clustering. The results showed an increasing trend in FFS/FMS publications, with the USA leading in both publications (n = 238) and citations (n = 2420). The most cited journal was the Journal of Plastic and Reconstructive Surgery. The results indicate a high growth rate, with an H-index of 34 and an average citation of 11.41 per article. Co-occurrence analysis revealed evolving keywords such as “forehead” (n = 52) and “quality of life” (n = 44). The timeline view illustrated the terms reflecting current areas of interest such as #patient satisfaction and #gender-affirming care. Conclusion: The study reveals the influence of countries, institutions, authors, and emerging trends, supporting the anticipation that FFS/FMS will be a critical field of study in the future. The findings contribute to understanding the global landscape of FFS/FMS research, facilitating informed decision-making for researchers, and clinicians in the field of maxillofacial surgery.

Background/Objectives: Odontogenic infections range from localized abscesses to life-threatening deep neck infections and are a frequent cause of emergency admission. We aimed to identify prognostic factors for postoperative complications after their surgical treatment. Methods: We retrospectively analyzed 194 adults (59.3% male) treated at the Department of Cranio-Maxillofacial Surgery in Cracow between 2020 and 2025. The primary outcome was any postoperative complication, graded by the Clavien–Dindo classification and dichotomized into minor (grade I–II) and major (grade ≥ III). Prolonged hospitalization and prolonged irrigation (>7 days) were secondary outcomes. Pre-specified main factors (advanced age, diffuse phlegmonous spread, diabetes mellitus) and covariates (sex, maxillary location, systemic disease) were tested by uni- and multivariable logistic regression. Results: Comorbidities were present in 69.1%. Complications occurred in 49 patients (25.3%): 19 (9.8%) minor and 30 (15.5%) major, including 12 grade IV intensive-care events and two deaths (grade V). In multivariable analysis, diffuse phlegmonous spread independently predicted any complication (adjusted OR 11.7), major complication (OR 23.4), prolonged hospitalization (OR 5.02) and prolonged irrigation (OR 4.39; all p ≤ 0.004). Advancing age independently predicted major complications (OR 1.03 per year, p = 0.037). Both fatal cases shared phlegmon, maxillary location and diabetes. Conclusions: Diffuse phlegmonous spread was the principal prognostic factor across all adverse outcomes, with advancing age additionally predicting major complications. Because intensive-care admission occurred almost exclusively in phlegmon patients, this association is partly definitional. Early identification of diffuse spread and advanced age may support effective triage.

Radicular cysts (RCs) represent the most frequent inflammatory cystic lesions of the jaw, typically arising from non-vital teeth. While standard management via enucleation is well-documented, complex cases involving the anterior maxilla present significant surgical challenges due to their proximity to the nasal cavity floor (NCF) and the maxillary sinus floor (MSF). This report provides a comprehensive revision of a clinical case series involving seven patients (ages 17–50) treated with multimodal surgical and regenerative protocols. The patients were stratified into five distinct anatomical risk groups (A–E) based on the integrity of the bony boundaries and the presence of oronasal communications. The treatment strategies combined meticulous cyst enucleation with advanced regenerative techniques, including platelet-rich fibrin (PRF), allogeneic and xenograft bone substitutes, and local flaps such as the buccal fat pad (BFP). The results across all seven cases demonstrated favorable clinical and radiographic outcomes, with no instances of oronasal fistula formation or recurrence during follow-up periods ranging from 12 months to three years. This report emphasizes the necessity of structured anatomical stratification and multimodal planning to ensure scientific precision and surgical predictability in the management of complex maxillary lesions. The differences between approaches towards the nasal cavity and maxillary sinus have to be highlighted. Further studies with larger cohorts are warranted to evaluate the long-term outcomes of different treatment modalities.