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用生成性人工智能和基础模型的力量彻底改变数字病理学

Asim Waqas1, Marilyn M Bui2, Eric F Glassy3

  • 1Department of Machine Learning, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida; Department of Electrical Engineering, University of South Florida, Tampa, Florida.

Laboratory investigation; a journal of technical methods and pathology
|September 27, 2023
PubMed
概括

基础模型和生成人工智能为数字病理学提供了变革性的潜力. 这些先进的AI系统可以克服特定任务模型的局限性,提高像图像分析和诊断等任务的效率和客观性.

关键词:
人工智能的人工智能是人工智能.计算和数字病理学基础模型 基础模型大型语言模型.多式联运数据是多式联运数据.视觉语言模型 视觉语言模型

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Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...