医疗保健预测分析的机器学习方法

Appoorva Bansal, Anand Kr. Shukla, S. Bansal
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引用次数: 0

摘要

当我们处理大量数据时,我们不得不期待机器学习、预测分析、模式识别等技术。特别是在卫生部门,机器学习发展太快,也给生产带来了挑战。对于预测未来,机器学习算法起着重要的作用,通过它,系统可以随着时间的推移而学习并变得富有成效。机器学习的方法和技术在各个领域都有应用。其中,医疗保健是一个需要大量预测技术帮助的领域。通过卫生保健中的预测分析技术,可以有效地管理患者的有效治疗和风险因素,提高卫生保健质量。根据现代情况,在成本和其他因素方面,医疗保健需要大幅改善。目前,医疗保健部门在电子数据管理、根据症状预测疾病、患者分类、基于计算机的诊断、风险因素等方面面临问题。这些挑战可以在机器学习工具和技术的帮助下解决。本文重点研究了用于预测分析的各种机器学习方法。它包括了机器学习的各个应用领域,但主要强调了机器学习在医疗保健领域的作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine Learning Methods for Predictive Analytics in Health Care
When we are dealing with the huge amount of data we have to look forward to the techniques like machine learning, predictive analysis, pattern recognition etc. Specially in the health sector machine learning is growing too fast and also give productive challenges. For predicting future, machine learning algorithm plays an important role, through which system can learn and become productive by the passing time. Method and Techniques of Machine Learning are used in various fields. Among those Health care is of the field which takes lots of help from the techniques of predictions. Through the techniques of predictive analysis in health care, effective treatment and risk factor can be managed effectively among patients and improve the quality of health care. As per the modern scenario, there is a need of huge improvement in the healthcare in term of cost and other factors. Today healthcare sector faces problem in the electronic data management, disease prediction as per the symptoms, patient classification, computer based diagnosis, risk factor etc. These challenges can be solved with the help of the machine learning tools and techniques. In this paper the focus to study the various machine learning method for the predictive analysis. Its includes various application area of machine learning, but mainly highlighting the role of machine learning in health care sectors.
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