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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
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牙科应用人工智能:新兴的数据模式和建模方法.

Balazs Feher1,2,3,4, Camila Tussie1, William V Giannobile1

  • 1Department of Oral Medicine, Infection, and Immunity, Harvard School of Dental Medicine, Boston, MA, United States.

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人工智能 (AI),特别是机器学习 (ML),正在彻底改变牙科医学. 人工智能增强了诊断,风险预测和临床决策,改善了口腔健康结果和研究效率.

关键词:
人工智能是一种人工智能.牙科 牙科医学 牙科医学牙科放射学 牙科放射学诊断建模 诊断建模生成式建模生成式建模机器学习是机器学习.预测模型的预测模型.

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科学领域:

  • 牙科医学 牙科医学
  • 人工智能的人工智能
  • 机器学习 机器学习

背景情况:

  • 人工智能 (AI) 和机器学习 (ML) 越来越多地融入医疗学科,包括牙科.
  • 机器学习识别数据中的模式,反映人类的学习过程.
  • 目前的临床牙科利用ML进行诊断,风险分层和决策支持,以提高护理.

研究的目的:

  • 从ML的角度提供对牙科医学AI应用的全面概述.
  • 探索AI在牙科诊断,预后和生成任务中的作用.
  • 介绍牙科中的数据模式及其与人工智能方法的兼容性.

主要方法:

  • 对牙科医学中AI和ML的当前文献的综述.
  • 在诊断,预后和生成任务中分析AI应用程序.
  • 检查数据模式及其适合人工智能集成的情况.

主要成果:

  • 人工智能,尤其是机器学习,正在显著推进牙科诊断,风险预测和临床决策支持.
  • 在牙科研究中,ML被广泛采用,从基础科学到临床研究.
  • 牙科中的各种数据模式与不同的AI技术兼容.

结论:

  • 人工智能为改善口腔卫生保健效率,结果和减少差异提供了巨大的潜力.
  • 人工智能在牙科领域的实施存在挑战和局限性,但正在解决.
  • 人工智能在牙科医学中的未来可能性是广泛的,需要仔细考虑.