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在中风预测中最有效的机器学习算法:系统性审查

Farkhondeh Asadi¹, Milad Rahimi², Amir Hossein Daeechini¹

¹Department of Health Information Technology and Management School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences Tehran Iran.

Health science reports

|October 2, 2024

概括

机器学习算法显示出对中风预测的前景,随机森林是高度有效的. 需要继续进行研究,以提高各种数据集的准确性和可靠性.

科学领域:

医疗信息学医疗信息学
计算神经科学是一种神经科学.
公共卫生公共卫生

背景情况:

卒中是全球死亡和残疾的主要原因之一.
有效的中风预测对于减轻其对生活质量的严重影响至关重要.

研究的目的:

系统地审查用于中风预测的机器学习算法.
识别和比较2019年至2023年8月期间发布的最有效的算法.

主要方法:

在PubMed,Scopus,Web of Science和IEEE进行系统的文献搜索.
包含的关键词包括了关键词.

主要成果:

分析了20篇文章,在25%的研究中确定随机森林 (RF) 是最有效的算法.
其他有效的算法包括支持矢量机器 (SVM),XGBOOST和人工神经网络 (ANN).

结论:

对于中风预测的机器学习已经迅速发展,精度得到了显著的改进.
目前没有一个模型可以达到完美的准确性;数据集和样本大小的变化会影响性能.
未来的研究应该标准化数据集和样本大小,以获得更可靠的中风预测模型.

关键词:

人工智能的人工智能是人工智能.机器学习是机器学习.预测预测预测预测一次性中风中风中风中风中风

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相关概念视频

Regression Analysis

Regression Analysis

Regression analysis is a statistical tool that describes a mathematical relationship between a dependent variable and one or more independent variables.
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:

Classification of Systems-I

Classification of Systems-I

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:

Classification of Systems-II

Classification of Systems-II

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,