基于机器学习算法的心脏病自动诊断系统的发展:现状与展望

Somnath B. Thigale et al.
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引用次数: 0

摘要

如今,心脏病是全球最常见和最严重的疾病之一,也是导致死亡的主要原因之一。心脏病预测是一项非常关键和具有挑战性的任务。机器学习(ML)是医疗保健领域的一项重要技术。这样的系统协助(而不是取代)医生解释疾病。使用机器学习算法的心脏病自动诊断系统是众多研究人员关注的热门系统之一,是进一步研究的热点领域。近十年来,人们对利用机器学习算法设计心脏病自动诊断系统进行了广泛的研究。设计一个高精度的心脏病诊断系统可以帮助挽救生命。本文全面综述了机器学习算法在心脏病自动诊断系统领域的发展现状和趋势。该调查详细介绍了心脏病诊断或预测的总体进展,并对预测系统中使用的数据预处理、特征提取算法和分类器进行了有效的回顾。讨论了一些尚未解决的问题和挑战,这些问题和挑战相对较少受到关注,突出了心脏病诊断的未来前景,并为进一步的研究提供了指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development of Automated Heart Disease Diagnosis System Using Machine Learning Algorithm: Current Status And Future Prospects
Nowadays Heart disease is one of the most common and serious disease as it is the one of major cause of death globally. Heart disease prediction is very critical and challenging task. Machine Learning (ML) an important technique in the field of Health care applications. Such systems assist (Not replaces) doctors in the interpretation of diseases. Automated Heart Disease Diagnosis System using Machine Learning Algorithm is amongst popular systems which have attracted the attention of numerous researchers, making it a thrust area for further investigations. In last decade, extensive investigations have been contributed to design Automated Heart Disease Diagnosis System using Machine Learning Algorithm. Designing a heart disease diagnosis system with high accuracy can help to save lives. A comprehensive survey of the developments and current trends in area of Automated Heart Disease Diagnosis System using Machine Learning algorithms is presented in this paper. The survey details the overall advancements in diagnosis or prediction of heart disease and an effective review of pre-processing of data, feature extraction algorithms and the classifiers used in prediction system. Few unaddressed issues and challenges that have comparatively received meagre attention are discussed highlighting the future prospects of Heart Disease Diagnosis and providing pointers to the further research.
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