一个不可思议的人工智能驱动的决策支持系统用于中风后的移动性评估.
Jin Cheng Liaw1, Dominik Raab1, Malte Weber1
1Chair of Mechanics and Robotics, University of Duisburg-Essen, Duisburg, Germany.
概括
机器学习模型从步态数据准确评估中风患者的运动能力,有助于中风后的评估. 这项技术通过提供客观的反关于移动障碍的信息来支持治疗师.
科学领域:
- 神经学 神经学
- 康复医学 康复医学 康复医学
- 人工智能的人工智能
背景情况:
- 长期的运动障碍是中风幸存者的常见后果,需要广泛的医疗和物理治疗.
- 准确评估治疗成功至关重要,但由于移动障碍的复杂性和对专家临床服务的日益增长的需求,这是一个挑战.
- 人员短缺和患者数量的增加在提供足够的中风后护理和移动性评估方面带来了重大挑战.
研究的目的:
- 研究机器学习算法在复制专家级移动性评估中的有效性,使用中风患者的步态数据.
- 开发一个支持中风后移动性评估的自动化系统,并为评估生成提供可解释的反.
- 为应对人力资源短缺和康复机构患者负担所带来的挑战.
主要方法:
- 100名半性中风患者接受了临床评估和仪器步行分析.
- 一个跨学科的专家委员会根据全面的步态数据分配了中风移动性得分.
- 两个回归模型,一个决策树和一个多层感知神经网络,在680个提取的步态特征上受过训练.
主要成果:
- 这两种机器学习模型在复制专家移动性得分时都表现出良好的至非常好的确定系数.
- 可解释的决策树和神经网络解释确定了对于移动性评估至关重要的关键步行特征.
- 模型产生的自动评估与专家评估有很强的一致性.
结论:
- 机器学习模型可以从中风患者的步态数据准确地复制专家的移动性评估.
- 开发的系统提供客观的反,并支持治疗师在评估中风后的移动性.
- 人工智能系统和临床医生之间的协同合作可以提高诊断质量,并在中风康复中实现治疗目标.
相关概念视频
01:14Decision Making: Traditional Method
The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
01:20Decision Making
Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...
Automatic decision-making is fast, intuitive, and relies on gut feelings...