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相关概念视频

Teeth01:15

Teeth

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The formation of teeth, also known as odontogenesis, is a complex process that begins in utero, around the sixth week of embryonic development. There are three stages to this process: the bud stage, the cap stage, and the bell stage.
In the bud stage, the tooth germ (an aggregation of cells) starts to form in the developing jawbone. During the cap stage, the tooth germ differentiates into enamel organ, dental papilla, and dental sac, which will later develop into the tooth's enamel, dentin...
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Tooth Anatomy01:21

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The human tooth enables us to eat a variety of foods, speak clearly, and even aid in shaping our faces. Teeth are composed of various elements that work together. Here's a detailed look at the anatomy of a human tooth.
The Crown, Neck, and Root
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The oral cavity, or the mouth, is a complex structure in humans that plays a vital role in our day-to-day lives. Its role is not only in chewing and swallowing food; it also plays a role in speech and facial expressions.
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自然语言处理:牙科的机遇和挑战

Martha Büttner1, Ulf Leser2, Lisa Schneider1

  • 1Department of Oral Diagnostics, Digital Health and Health Services Research, Charité - Universitätsmedizin Berlin, Germany.

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概括

自然语言处理 (NLP) 在牙科中为症状分类和聊天机器人等任务提供了巨大的潜力. 然而,数据需求和可解释性的挑战目前限制了它在牙科领域的广泛采用.

关键词:
人工智能的人工智能是人工智能.大数据就是大数据.诊断系统的诊断系统.信息学是一种信息学.实践管理的管理实践.

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科学领域:

  • * 计算机科学和语言学
  • * 自然语言处理 (NLP)

背景情况:

  • *NLP使机器能够处理和理解人类语言.
  • * 牙科的应用包括文本分类和自然语言生成/理解.
  • *NLP可以分析大量的文本以获得疾病洞察力和个性化护理.

研究的目的:

  • * 总结NLP在牙科中的应用.
  • * 概述NLP在牙科领域的局限性.
  • * 呼吁社区采取行动,改善牙科NLP.

主要方法:

  • *对现有文献进行叙述性回顾.
  • *对当前NLP应用和技术的分析.
  • * 识别牙科NLP的挑战和潜在解决方案.

主要成果:

  • * 关键的NLP应用包括症状分类,临床聊天机器人和语音识别用于记录.
  • *先进的NLP技术,如循环神经网络和变压器,显示出有希望的结果,但它们需要大量的数据.
  • *目前的牙科NLP研究主要使用基于规则的解决方案来处理狭窄的任务.

结论:

  • *NLP即将成为各种牙科应用中的基石.
  • *通过联合学习,转移学习或数据共享来克服局限性至关重要.
  • * 解决可解释性,可复制性和可概括性的挑战是医疗器械批准所必需的.