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Anesthesia research in the artificial intelligence era
Anesth Pain Med 2018;13(3):248-55
Published online July 31, 2018
© 2018 The Korean Society of Anesthesiologists.

Hyung-Chul Lee and Chul-Woo Jung
Department of Anesthesiology and Pain Medicine, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Korea
Correspondence to: Chul-Woo Jung, M.D. Department of Anesthesiology and Pain Medicine, Seoul National University College of Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul 03080, Korea Tel: 82-2-2072-0640 Fax: 82-2-747-5639 E-mail: spss@snuh.org ORCID http://orcid.org/0000-0001-7876-8659
Received May 29, 2018; Accepted June 4, 2018.
cc This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
A noteworthy change in recent medical research is the rapid increase of research using big data obtained from electrical medical records (EMR), order communication systems (OCS), and picture archiving and communication systems (PACS). It is often difficult to apply traditional statistical techniques to research using big data because of the vastness of the data and complexity of the relationships. Therefore, the application of artificial intelligence (AI) techniques which can handle such problems is becoming popular. Classical machine learning techniques, such as k-means clustering, support vector machine, and decision tree are still efficient and useful for some research problems. The deep learning techniques, such as multi-layer perceptron, convolutional neural network, and recurrent neural network have been spotlighted by the success of deep belief networks and convolutional neural networks in solving various problems that are difficult to solve by conventional methods. The results of recent research using artificial intelligence techniques are comparable to human experts. This article introduces technologies that help researchers conduct medical research and understand previous literature in the era of AI.
Key Words : Artificial intelligence, Big data, Machine learning, Medical research.


July 2018, 13 (3)
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