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人工智能方法及其在糖尿病中的应用。

Artificial Intelligence Methodologies and Their Application to Diabetes.

作者信息

Rigla Mercedes, García-Sáez Gema, Pons Belén, Hernando Maria Elena

机构信息

1 Endocrinology and Nutrition Department, Parc Tauli University Hospital, Sabadell, Spain.

2 Bioengineering and Telemedicine Centre, Universidad Politécnica de Madrid, Spain.

出版信息

J Diabetes Sci Technol. 2018 Mar;12(2):303-310. doi: 10.1177/1932296817710475. Epub 2017 May 25.

Abstract

In the past decade diabetes management has been transformed by the addition of continuous glucose monitoring and insulin pump data. More recently, a wide variety of functions and physiologic variables, such as heart rate, hours of sleep, number of steps walked and movement, have been available through wristbands or watches. New data, hydration, geolocation, and barometric pressure, among others, will be incorporated in the future. All these parameters, when analyzed, can be helpful for patients and doctors' decision support. Similar new scenarios have appeared in most medical fields, in such a way that in recent years, there has been an increased interest in the development and application of the methods of artificial intelligence (AI) to decision support and knowledge acquisition. Multidisciplinary research teams integrated by computer engineers and doctors are more and more frequent, mirroring the need of cooperation in this new topic. AI, as a science, can be defined as the ability to make computers do things that would require intelligence if done by humans. Increasingly, diabetes-related journals have been incorporating publications focused on AI tools applied to diabetes. In summary, diabetes management scenarios have suffered a deep transformation that forces diabetologists to incorporate skills from new areas. This recently needed knowledge includes AI tools, which have become part of the diabetes health care. The aim of this article is to explain in an easy and plane way the most used AI methodologies to promote the implication of health care providers-doctors and nurses-in this field.

摘要

在过去十年中,持续葡萄糖监测和胰岛素泵数据的加入改变了糖尿病管理模式。最近,通过腕带或手表可以获取各种各样的功能和生理变量,如心率、睡眠时间、步数和运动量等。未来还将纳入新的数据,如水合作用、地理位置和气压等。所有这些参数经过分析后,对患者和医生的决策支持都可能有所帮助。类似的新情况在大多数医学领域都已出现,以至于近年来,人们对人工智能(AI)方法在决策支持和知识获取方面的开发与应用越来越感兴趣。由计算机工程师和医生组成的多学科研究团队越来越常见,这反映了在这个新课题上合作的必要性。作为一门科学,人工智能可以定义为使计算机能够完成如果由人类来做则需要智能的事情的能力。越来越多与糖尿病相关的期刊开始收录专注于应用于糖尿病的人工智能工具的出版物。总之,糖尿病管理模式经历了深刻变革,这迫使糖尿病专家融入新领域的技能。这种最近所需的知识包括人工智能工具,它们已成为糖尿病医疗保健的一部分。本文的目的是以简单易懂的方式解释最常用的人工智能方法,以促进医疗保健提供者(医生和护士)在该领域的参与。

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