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Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

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Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
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Classification of Systems-II01:31

Classification of Systems-II

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Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
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Classification of Systems-I01:26

Classification of Systems-I

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Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
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Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
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Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
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The meaning of illness is individualized to each person who experiences an alteration in health. In contrast, disease is a medical term indicating a pathological change in the structure and function of the body or mind. It is a condition that has specific symptoms and boundaries.
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Portable Intermodal Preferential Looking IPL: Investigating Language Comprehension in Typically Developing Toddlers and Young Children with Autism
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多标签短拍子ICD编码作为自行回归生成与快速提示.

Zhichao Yang1, Sunjae Kwon1, Zonghai Yao1

  • 1College of Information and Computer Sciences, University of Massachusetts Amherst.

Proceedings of the ... AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence
|August 28, 2023
PubMed
概括

这项研究将国际疾病分类 (ICD) 的自动编码转换为文本生成,显著提高了不常见代码的性能. 这种新方法提高了几次拍摄和完整的ICD代码分配任务的准确性.

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科学领域:

  • 医疗信息学 医疗信息学
  • 自然语言处理自然语言处理.
  • 机器学习 机器学习

背景情况:

  • 自动国际疾病分类 (ICD) 编码对于医疗记录分析至关重要,但面临着高维多标签分配和罕见代码的长尾问题所带来的挑战.
  • 现有的方法很难有效地赋予罕见但具有临床意义的ICD代码,这影响了医疗编码的完整性和准确性.

研究的目的:

  • 通过将其重新定义为自动回归生成任务来解决自动ICD编码的长尾挑战.
  • 开发一种新型模型,生成文本描述以推断ICD代码,提高常见和罕见代码的准确性.

主要方法:

  • 引入了一个新的预训练目标,使用医生使用的SOAP笔记结构来生成诊断和程序.
  • 开发了一个模型,生成低维文本描述,而不是直接预测高维ICD代码.
  • 设计了一个新的提示模板用于多标签分类和一个集体学习器与交叉注意力重排名器.

主要成果:

  • 用Prompt (GPsoap) 模型的生成在MIMIC-III-few基准上获得了30.2的宏F1得分,超过了以前的最先进 (SOTA) 模型.
  • 在MIMIC-III全基准测试中,集体学习者将宏观F1从10.4提高到14.6,微型F1从58.2提高到59.1.

结论:

  • 将ICD编码转化为自回归生成任务有效地解决了长尾挑战.
  • 拟议的GPsoap模型和集体学习器在自动ICD编码准确性方面提供了实质性的改进,特别是在不常见的代码中.