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Updated: Sep 19, 2025

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基于状态空间模型的自动放射学报告生成

Duo Zhang, Yun Tan, Jiaohua Qin

    IEEE journal of biomedical and health informatics
    |June 16, 2025
    PubMed
    概括

    这项研究引入了一种新的AI方法,使用Self-Attention Mamba和Cross-Attention Mamba模块来更快,更准确地从X射线生成放射学报告. 这种方法提高了效率,并通过更好地检测微妙的病理,减少了患者的等待时间.

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    相关概念视频

    State Space Representation01:27

    State Space Representation

    The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
    Consider an RLC circuit, a...
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    Transfer Function to State Space01:23

    Transfer Function to State Space

    State-space representation is a powerful tool for simulating physical systems on digital computers, necessitating the conversion of the transfer function into state-space form. Consider an nth-order linear differential equation with constant coefficients, like those encountered in an RLC circuit. The state variables are selected as the output and its n−1 derivatives. Differentiating these variables and substituting them back into the original equation produces the state equations.
    In an...
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    State Space to Transfer Function01:21

    State Space to Transfer Function

    The conversion of state-space representation to a transfer function is a fundamental process in system analysis. It provides a method for transitioning from a time-domain description to a frequency-domain representation, which is crucial for simplifying the analysis and design of control systems.
    The transformation process begins with the state-space representation, characterized by the state equation and the output equation. These equations are typically represented as:
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    Linear Approximation in Time Domain01:21

    Linear Approximation in Time Domain

    Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
    For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
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