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Crosslinked Versus Non-Crosslinked Resorbable Collagen Membranes for Periodontal Regeneration: A Multicenter, Randomized, Double-Blind, Non-Inferiority Clinical Trial.
J Periodontal Res
January 2025
Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Aim: This study aimed to evaluate and compare the results of combination therapy involving bone grafting and two different resorbable collagen membranes in 1-, 2- and 3-wall infrabony defects.
Methods: A total of 174 patients with infrabony defects (≥ 7 mm periodontal probing depth) were randomized to receive deproteinized bovine bone mineral (DBBM) with either a native porcine non-crosslinked collagen membrane (N-CM, control, n = 87) or a novel porcine crosslinked collagen membrane (C-CM, test, n = 87). Clinical parameters, including periodontal probing depth (PPD), clinical attachment level (CAL), and gingival recession (GR), were recorded at baseline, 12 weeks, and 24 weeks.
Cowden Syndrome and Oral Lesions: A Case Report Using MLPA.
Am J Case Rep
January 2025
Research Institute of Dentistry, Department of Integral Dental Clinics, University Center of Health Sciences, Universidad de Guadalajara, Guadalajara, Mexico.
BACKGROUND Cowden syndrome is a genetic disorder that predisposes individuals to cancer and is characterized by hamartomas derived from 3 germ layers. Although the clinical signs can be pathognomonic, diagnosis is often aided by biopsies, histopathological examination of oral and cutaneous lesions, and genetic studies, including multiple ligation-dependent probe amplification (MLPA). CASE REPORT We report a case of a 35-year-old woman who manifested with multiple lesions in the buccal mucosa, dorsum of the tongue, and gums, along with papillomatous papules on her facial skin and the dorsal surfaces of her hands.
View Article and Find Full Text PDFBayesian network for predicting mandibular third molar extraction difficulty.
BMC Oral Health
January 2025
Sub-Institute of Public Safety Standardization, China National Institute of Standardization, No.4 Zhichun Road, Haidian District, Beijing, 100191, PR China.
Background: This study aimed to establish a model for predicting the difficulty of mandibular third molar extraction based on a Bayesian network to meet following requirements: (1) analyse the interaction of the primary risk factors; (2) output quantitative difficulty-evaluation results based on the patient's personal situation; and (3) identify key surgical points and propose surgical protocols to decrease complications.
Methods: Relevant articles were searched to identify risk factors. Clinical knowledge and experience were used to analyse the risk factors to establish the Bayesian network.
Evaluation of different artificial intelligence applications in responding to regenerative endodontic procedures.
BMC Oral Health
January 2025
Department of Endodontics, Faculty of Dentistry, Marmara University, Başıbüyük, Başıbüyük Yolu Marmara Üniversitesi Başıbüyük Sağlık Yerleşkesi 9/3, Başıbüyük - Maltepe, PO Box: 34854, İstanbul, Turkey.
Introduction: The integration of artificial intelligence (AI) technologies in healthcare is revolutionizing the workflows of healthcare professionals, enabling faster and more accurate patient treatment. This study aims to evaluate the accuracy of responses provided by different AI chatbots to questions that dentists might ask regarding regenerative endodontic treatment (RET), a procedure that shows promising biological healing potential.
Methods: A total of 23 questions related to RET procedures were developed based on the American Association of Endodontists (AAE) 2022 guidelines.
Evaluation of a context-aware chatbot using retrieval-augmented generation for answering clinical questions on medication-related osteonecrosis of the jaw.
J Craniomaxillofac Surg
January 2025
Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
The potential of large language models (LLMs) in medical applications is significant, and Retrieval-augmented generation (RAG) can address the weaknesses of these models in terms of data transparency and scientific accuracy by incorporating current scientific knowledge into responses. In this study, RAG and GPT-4 by OpenAI were applied to develop GuideGPT, a context aware chatbot integrated with a knowledge database from 449 scientific publications designed to provide answers on the prevention, diagnosis, and treatment of medication-related osteonecrosis of the jaw (MRONJ). A comparison was made with a generic LLM ("PureGPT") across 30 MRONJ-related questions.
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