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Issues And Trends In Healthcare Delivery System01:29

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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
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Trends in nursing are multifactorial and associated with changes in society, within the nursing profession, and in other professions. Notably, telehealth and remote nursing contribute to successful healthcare delivery for numerous patients and help reduce stress for nurses due to nursing shortages. Nurses can reach patients, monitor their conditions, and interact with them using computers, audio, visual accessories, and telephones—for example, remote patient monitoring systems. Likewise,...
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Constructing and Visualizing Models using Mime-based Machine-learning Framework
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机器学习:趋势,前景和前景

M I Jordan1, T M Mitchell2

  • 1Department of Electrical Engineering and Computer Sciences, Department of Statistics, University of California, Berkeley, CA, USA. jordan@cs.berkeley.edu tom.mitchell@cs.cmu.edu.

Science (New York, N.Y.)
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PubMed
概括
此摘要是机器生成的。

机器学习使计算机能够从经验中学习,推动人工智能和数据科学的进步. 它的数据密集型方法正在改变医疗保健和金融等各个领域的决策.

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科学领域:

  • 计算机科学
  • 统计数据
  • 人工智能
  • 数据科学

背景情况:

  • 机器学习专注于通过数据暴露来提高性能的系统.
  • 这是一个快速发展的技术领域.
  • 进步是由新的算法,理论见解和增加的数据可用性推动的.

研究的目的:

  • 提供机器学习的作用和影响的概述.
  • 突出最近进步背后的驱动力.
  • 为了说明机器学习方法的广泛应用.

主要方法:

  • 开发新的学习算法和理论框架.
  • 充分利用大量数据的可用性.
  • 使用低成本计算能力的进步.

主要成果:

  • 在机器学习能力方面取得了重大进展.
  • 在不同领域广泛采用数据密集型方法.
  • 加强基于证据的决策.

结论:

  • 机器学习是计算机科学和统计学交叉的关键领域.
  • 它的应用正在彻底改变从医疗到营销的各个行业.
  • 该领域的增长与数据和计算资源密切相关.