文章基本信息

标题：Discovering hidden information in biosignals from patients using artificial intelligence
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作者：Dukyong Yoon ; Jong-Hwan Jang ; Byung Jin Choi 等
期刊名称：Korean Journal of Anesthesiology
印刷版ISSN：2005-6419
出版年度：2020
卷号：73
期号：4
页码：275-284
DOI：10.4097/kja.19475
语种：English
出版社：The Korean Society of Anesthesiologists,
摘要：Biosignals such as electrocardiogram or photoplethysmogram are widely used for determining and monitoring the medical condition of patients. It was recently discovered that more information could be gathered from biosignals by applying artificial intelligence (AI). At present, one of the most impactful advancements in AI is deep learning. Deep learning-based models can extract important features from raw data without feature engineering by humans, provided the amount of data is sufficient. This AI-enabled feature presents opportunities to obtain latent information that may be used as a digital biomarker for detecting or predicting a clinical outcome or event without further invasive evaluation. However, the black box model of deep learning is difficult to understand for clinicians familiar with a conventional method of analysis of biosignals. A basic knowledge of AI and machine learning is required for the clinicians to properly interpret the extracted information and to adopt it in clinical practice. This review covers the basics of AI and machine learning, and the feasibility of their application to real-life situations by clinicians in the near future.