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相关实验视频

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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
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一般医疗人工智能的基础模型

Michael Moor1, Oishi Banerjee2, Zahra Shakeri Hossein Abad3

  • 1Department of Computer Science, Stanford University, Stanford, CA, USA.

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|April 12, 2023
PubMed
概括

我们介绍了能够用最少的数据执行各种医疗任务的通用医疗人工智能 (AI) 模型. 这些灵活的人工智能系统解释各种数据类型,

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科学领域:

  • 医疗人工智能
  • 在医疗保健中的机器学习

背景情况:

  • 人工智能 (AI) 的快速发展使得新的医疗应用成为可能.
  • 目前的人工智能模型通常需要广泛的特定任务的标记数据.

研究的目的:

  • 提出一个新的范式:通用医学AI (GMAI).
  • 概述GMAI模型的功能和要求.

主要方法:

  • 在大型,多样化的数据集上开发自主监督学习.
  • 实现多模式医疗数据的灵活解释 (成像,电子健康记录,基因组学,文本等). ) 的情况.

主要成果:

  • GMAI模型可以在很少或没有特定任务数据的情况下执行各种任务.
  • GMAI可以产生表达式输出,如自由文本解释和图像注释.
  • 确定了GMAI的高影响性应用和必要的技术能力.

结论:

  • 它代表了医疗人工智能能力的重大转变.
  • 将需要新的人工智能监管,验证和数据收集方法.