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5岁以下腭裂患儿术后腭咽闭合功能变化规律的研究 被引量:3
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作者 尹恒 黄汉尧 +3 位作者 郭春丽 王希 石冰 李精韬 《华西口腔医学杂志》 CAS CSCD 北大核心 2020年第1期48-53,共6页
目的探讨低龄腭裂患儿术后腭咽闭合功能恢复规律,及与年龄、腭裂类型和不同复诊时间等因素的相关关系。方法本研究纳入有2次以上复诊记录的5岁以下腭裂患者,回顾其术后腭咽闭合功能的连续性评估结果,分别进行单因素和多因素logistic回... 目的探讨低龄腭裂患儿术后腭咽闭合功能恢复规律,及与年龄、腭裂类型和不同复诊时间等因素的相关关系。方法本研究纳入有2次以上复诊记录的5岁以下腭裂患者,回顾其术后腭咽闭合功能的连续性评估结果,分别进行单因素和多因素logistic回归检验,分析术后腭咽闭合功能变化的规律及影响因素。结果共纳入165例患者,其中31例患者出现前后腭咽闭合功能不一致,即初次复诊判定为腭咽闭合不全(VPI)而在二次复诊转为腭咽闭合完全(VPC),占总数18.79%;134例患者前后复诊腭咽闭合功能一致。腭咽闭合功能前后一致的患者平均年龄显著小于不一致的患者。手术年龄越小,在初次复诊时,患者的腭咽闭合功能更容易达到稳定。患者在术后15、28、40个月时,腭咽闭合功能达到稳定的比例为80%、90%、95%。结论腭裂术后腭咽闭合功能的恢复是一个动态过程,早期的VPI可能发展为VPC,但VPC不会再转变为VPI。复诊时间是腭咽闭合功能评估结果前后一致性最重要的相关因素,选择合适的复诊时间,有利于获得稳定准确的腭咽闭合功能评估结果。 展开更多
关键词 腭裂 腭咽闭合功能 多因素LOGISTIC回归分析
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ChatGPT for shaping the future of dentistry: the potential of multi-modal large language model 被引量:10
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作者 hanyao huang Ou Zheng +8 位作者 Dongdong Wang Jiayi Yin Zijin Wang Shengxuan Ding Heng Yin Chuan Xu Renjie Yang Qian Zheng Bing Shi 《International Journal of Oral Science》 SCIE CAS CSCD 2023年第3期377-389,共13页
The ChatGPT,a lite and conversational variant of Generative Pretrained Transformer 4(GPT-4)developed by OpenAI,is one of the milestone Large Language Models(LLMs)with billions of parameters.LLMs have stirred up much i... The ChatGPT,a lite and conversational variant of Generative Pretrained Transformer 4(GPT-4)developed by OpenAI,is one of the milestone Large Language Models(LLMs)with billions of parameters.LLMs have stirred up much interest among researchers and practitioners in their impressive skills in natural language processing tasks,which profoundly impact various fields.This paper mainly discusses the future applications of LLMs in dentistry.We introduce two primary LLM deployment methods in dentistry,including automated dental diagnosis and cross-modal dental diagnosis,and examine their potential applications.Especially,equipped with a cross-modal encoder,a single LLM can manage multi-source data and conduct advanced natural language reasoning to perform complex clinical operations.We also present cases to demonstrate the potential of a fully automatic Multi-Modal LLM AI system for dentistry clinical application.While LLMs offer significant potential benefits,the challenges,such as data privacy,data quality,and model bias,need further study.Overall,LLMs have the potential to revolutionize dental diagnosis and treatment,which indicates a promising avenue for clinical application and research in dentistry. 展开更多
关键词 MODAL equipped operations
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Computational technology for nasal cartilage-related clinical research and application 被引量:9
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作者 Bing Shi hanyao huang 《International Journal of Oral Science》 SCIE CAS CSCD 2020年第3期183-198,共16页
Surgeons need to understand the effects of the nasal cartilage on facial morphology,the function of both soft tissues and hard tissues and nasal function when performing nasal surgery.In nasal cartilage-related surger... Surgeons need to understand the effects of the nasal cartilage on facial morphology,the function of both soft tissues and hard tissues and nasal function when performing nasal surgery.In nasal cartilage-related surgery,the main goals for clinical research should include clarification of surgical goals,rationalization of surgical methods,precision and personalization of surgical design and preparation and improved convenience of doctor–patient communication.Computational technology has become an effective way to achieve these goals.Advances in three-dimensional(3D)imaging technology will promote nasal cartilage-related applications,including research on computational modelling technology,computational simulation technology,virtual surgery planning and 3D printing technology.These technologies are destined to revolutionize nasal surgery further.In this review,we summarize the advantages,latest findings and application progress of various computational technologies used in clinical nasal cartilage-related work and research.The application prospects of each technique are also discussed. 展开更多
关键词 NASAL CLINICAL application
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