Over the last two decades there have been many changes in the basic concepts of periodontology, which have had profound effects on clinical practice. The aim of this series is to highlight the main areas of change and to assist the busy general practitioner in staying up-to-date. The first article deals with the current understanding of the histopathogenesis of gingivitis and periodontitis.
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Evaluating the image recognition capabilities of GPT-4V and Gemini Pro in the Japanese national dental examination.
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Division of Physiology, Department of Health Promotion, Kyushu Dental University, Kitakyushu, Japan.
Background/purpose: OpenAI's GPT-4V and Google's Gemini Pro, being Large Language Models (LLMs) equipped with image recognition capabilities, have the potential to be utilized in future medical diagnosis and treatment, ands serve as valuable educational support tools for students. This study compared and evaluated the image recognition capabilities of GPT-4V and Gemini Pro using questions from the Japanese National Dental Examination (JNDE) to investigate their potential as educational support tools.
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Hua Xi Kou Qiang Yi Xue Za Zhi
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State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Frontier Innovation Center for Dental Medicine Plus & West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China.
Geriatric oral health care encounters significant challenges with the increase in the proportion of older individuals. Age-related changes in the dentition, muscles, and joints result in a decline in objective masticatory function, subjective restoration requirements, and acceptability among the elderly population, with individual variations influenced by systemic health. Considering functional requirements, the adaptability of stomatognathic and systemic health conditions, health economics and other factors, the authors believe that it should not be limited to the conventional "one-to-one" strategy for replacing missing teeth in geriatric prosthodontics.
View Article and Find Full Text PDFDeep Learning for Age Estimation from Panoramic Radiographs: A Systematic Review and Meta-Analysis.
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Topic Group Dental Diagnostics and Digital Dentistry, ITU/WHO Focus Group AI on Health, Berlin, Germany; Clinic for Operative Dentistry and Periodontology, LMU Klinikum, Munich, Germany.
Introduction: Panoramic radiographs are widely used for age estimation in clinical and forensic domains. Conventionally, age estimation uses humans assessing tooth development and deducing the expected age from that. Deep learning may improve or substitute this traditional approach and allow age estimation at scale in routine settings.
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Perio-Implant Innovation Center, Institute for Integrated Oral, Craniofacial and Sensory Research and Department of Oral and Maxillofacial Implantology and National Clinical Research Center of Stomatology, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
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