Korean journal of women health nursing/Yeoseong geon'gang ganho hag'hoeji/Yeoseong geon-gang ganho hakoeji · 2020 · 47 citations · 8 references
ComputingComputer ScienceMaternal Health NursingArtificial IntelligenceMachine LearningWomen's Health NursingDeep LearningMachine Learning For Big DataNeural NetworksPredictive Health ModelingAi-based PracticeDeep Learning-based DiagnosisMachine Learning For Health MonitoringMachine Learning For HealthcareMachine Learning Prediction ModelsNursing Interventions ClassificationNursing Interventions TaxonomyRegistered Nurses
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.
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Introducing Artificial Intelligence Training in Medical Education
Ketan Paranjape, Michiel Schinkel, Rishi Panday et al. · JMIR Medical Education · 2019 · 614 citations · Full text
Xi Yang, Jiang Bian, Ruogu Fang et al. · Journal of the American Medical Informatics Association · 2019 · 80 citations · Full text