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人工智能在风湿病学中意味着什么?

Kunal Chandwar1, Durga Prasanna Misra1

  • 1Department of Clinical Immunology and Rheumatology, Sanjay Gandhi Postgraduate Institute of Medical Sciences (SGPGIMS), Lucknow, India.

Archives of rheumatology
|May 22, 2024
PubMed
概括

人工智能 (AI),包括机器学习和深度学习,在风湿病学中为诊断,预后和治疗发现提供了革命性的潜力. 虽然存在道德上的挑战,但人工智能

科学领域:

  • 人工智能 (AI) 是一种人工智能.
  • 机器学习 (ML) 是指机器学习.
  • 深度学习 (DL) 是指深度学习.
  • 大型语言模型 (LLM)

背景情况:

  • 人工智能涉及将类似人类的学习能力转移到计算机.
  • 机器学习使智能数据理解成为可能,而深度学习则利用神经网络进行图像/视频分析.
  • LLM 是近期人工智能的一种进步,它通过转换器将自我学习与深度学习相结合.

研究的目的:

  • 探索人工智能在风湿病学研究和医疗保健中的变革潜力.
  • 突出AI在临床决策,诊断和预测分析中的应用.
  • 讨论AI在分析复杂的生物数据和自动化管理任务方面的作用.

主要方法:

  • 利用机器学习进行临床诊断和决策支持.
  • 采用深度学习来分析放射学,PET和组织病理学图像.
  • 利用人工智能用于使用患者数据和可穿戴设备预测疾病爆发的建模.
  • 对预后标志物和治疗点分析大量的奥米克数据 (基因组学,转录组学,蛋白质组学,代谢组学).

主要成果:

  • 人工智能可以显著帮助临床诊断和决策过程.
关键词:
人工智能的人工智能是人工智能.深度学习是一种深度学习.图像分析机器学习机器学习类风湿病学 类风湿病学

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  • 深度学习通过医学图像分析提高了诊断准确度.
  • 人工智能有助于预测疾病爆发和识别新型预后标志物.
  • 人工智能在发现新的治疗点和自动化管理任务方面显示出潜力.

    • 结论:

    • AI,包括ML,DL和LLMs,准备彻底改变风湿病学.
    • 人工智能应用范围从增强的诊断和个性化治疗到行政效率.
    • 对人工智能滥用的伦理考虑至关重要,但将其整合到风湿病学中是不可避免的和有前途的.