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通过人工智能和机器学习应用程序提高医疗保健的成本、质量和可及性。

Improving Healthcare Cost, Quality, and Access Through Artificial Intelligence and Machine Learning Applications.

机构信息

Health Administration, College of Health Professions, Texas State University, San Marcos, Texas.

出版信息

J Healthc Manag. 2021;66(4):271-279. doi: 10.1097/JHM-D-21-00149.

Abstract

Since the early 1970s, technology has increasingly become integrated into the healthcare field. Today, artificial intelligence (AI) and machine learning (ML, a set of learning techniques used by AI) have the capacity to revolutionize the delivery of patient care. This essay examines the mechanics and processes of machine learning through discussion of deep learning and natural language processing and then discusses the application of these learning techniques in pattern recognition of malignant tumors in comparison to present methods of diagnostic imaging assessment. The discussion also covers the implications of AI assistive technology more broadly regarding ethical policy making, patient autonomy, and the healthcare Iron Triangle of cost, quality, and access. It concludes with the idea that failure to incorporate AI and ML techniques in healthcare may be malpractice.

摘要

自 20 世纪 70 年代初以来,技术越来越多地融入医疗保健领域。如今,人工智能 (AI) 和机器学习 (ML,人工智能使用的一系列学习技术) 有能力彻底改变患者护理的提供方式。本文通过讨论深度学习和自然语言处理来研究机器学习的机制和过程,然后讨论这些学习技术在恶性肿瘤模式识别方面的应用,与目前的诊断成像评估方法进行比较。讨论还涵盖了更广泛的人工智能辅助技术对伦理政策制定、患者自主权以及医疗保健成本、质量和可及性的“铁三角”的影响。最后提出了这样一种观点,即未能在医疗保健中纳入 AI 和 ML 技术可能是一种医疗事故。

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