Signal analysis of physiological recordings for decision support and outcome prediction in the paediatric intensive care unit

生理记录的信号分析，用于儿科重症监护病房的决策支持和结果预测

• 批准号: 2107746
• 金额: --
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2107746
• 关键词: Signal; analysis; physiological; recordings; decision

The core research topic that will be investigated during the 3-year period of this project is the development of signal processing and potentially machine learning algorithms for the analysis of neurological and cardiorespiratory signals collected at the bedside in paediatric intensive-care units. This will include methods to clean the signals, obtain relevant features, and finally predict outcomes.The main research topics investigated as part of this project will most likely include:1. Signal processing algorithms that ensure the successful extraction of data from monitoring signals.2. Machine learning algorithms that would try to identify patterns in the data and predict physiological effects in order to support clinical decision making.

在这个项目的3年期间，将调查的核心研究课题是信号处理和潜在的机器学习算法的发展，用于分析在儿科重症监护病房床边收集的神经和心肺信号。这将包括清洗信号，获得相关特征，并最终预测结果的方法。作为这个项目的一部分，调查的主要研究课题很可能包括：1。确保从监测信号中成功提取数据的信号处理算法。机器学习算法将试图识别数据中的模式并预测生理效应，以支持临床决策。