Jeong Geum Hee
School of Nursing and Research Institute in Nursing Science, Hallym University, Chuncheon, Korea.
Korean J Women Health Nurs. 2020 Mar 31;26(1):5-9. doi: 10.4069/kjwhn.2020.03.11. Epub 2020 Mar 17.
Artificial intelligence (AI), which includes machine learning and deep learning has been introduced to nursing care in recent years. The present study reviews the following topics: the concepts of AI, machine learning, and deep learning; examples of AI-based nursing research; the necessity of education on AI in nursing schools; and the areas of nursing care where AI is useful. AI refers to an intelligent system consisting not of a human, but a machine. Machine learning refers to computers' ability to learn without being explicitly programmed. Deep learning is a subset of machine learning that uses artificial neural networks consisting of multiple hidden layers. It is suggested that the educational curriculum should include big data, the concept of AI, algorithms and models of machine learning, the model of deep learning, and coding practice. The standard curriculum should be organized by the nursing society. An example of an area of nursing care where AI is useful is prenatal nursing interventions based on pregnant women's nursing records and AI-based prediction of the risk of delivery according to pregnant women's age. Nurses should be able to cope with the rapidly developing environment of nursing care influenced by AI and should understand how to apply AI in their field. It is time for Korean nurses to take steps to become familiar with AI in their research, education, and practice.
近年来,包括机器学习和深度学习在内的人工智能(AI)已被引入护理领域。本研究回顾了以下主题:人工智能、机器学习和深度学习的概念;基于人工智能的护理研究实例;护理院校开展人工智能教育的必要性;以及人工智能在护理领域的应用范围。人工智能是指一个非人类而是机器构成的智能系统。机器学习是指计算机无需明确编程就能学习的能力。深度学习是机器学习的一个子集,它使用由多个隐藏层组成的人工神经网络。建议教育课程应包括大数据、人工智能概念、机器学习算法和模型、深度学习模型以及编码实践。标准课程应由护理学会组织。人工智能在护理领域的一个应用实例是基于孕妇护理记录的产前护理干预,以及根据孕妇年龄基于人工智能预测分娩风险。护士应能够应对受人工智能影响的快速发展的护理环境,并应了解如何在其领域应用人工智能。韩国护士是时候采取措施,在研究、教育和实践中熟悉人工智能了。