CE: Nursing Orientation to Data Science and Machine Learning

大数据 医疗保健 护理部 心理学 数据科学 人工智能 工作(物理) 方向(向量空间) 知识管理 计算机科学 医学 数据挖掘 工程类 政治学 法学 机械工程 几何学 数学
作者
Roxanne O'Brien,Matt W. O'Brien
出处
期刊:American Journal of Nursing [Lippincott Williams & Wilkins]
卷期号:121 (4): 32-39 被引量:8
标识
DOI:10.1097/01.naj.0000742064.59610.28
摘要

Nurses collect, use, and produce data every day in countless ways, such as when assessing and treating patients, performing administrative functions, and engaging in strategic planning in their organizations and communities. These data are aggregated into large data sets in health care systems, public and private databases, and academic research settings. In recent years the machines used in this work (computer hardware) have become increasingly able to analyze large data sets, or "big data," at high speed. Data scientists use machine learning tools to aid in analyzing this big data, such as data amassed from large numbers of electronic health records. In health care, predictions for patient outcomes has become a focus of research using machine learning. It's important for nurses and nurse administrators to understand how machine learning has changed our ways of thinking about data and turning data into knowledge that can improve patient care. This article provides an orientation to machine learning and data science, offers an understanding of current challenges and opportunities, and describes the nursing implications for nurses in various roles.

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