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http://dx.doi.org/10.7742/jksr.2022.16.4.453

Trends in the Use of Artificial Intelligence in Medical Image Analysis  

Lee, Gil-Jae (Department of Biomedical Engineering, Graduate School of Chungbuk National University)
Lee, Tae-Soo (Department of Biomedical Engineering, Graduate School of Chungbuk National University)
Publication Information
Journal of the Korean Society of Radiology / v.16, no.4, 2022 , pp. 453-462 More about this Journal
Abstract
In this paper, the artificial intelligence (AI) technology used in the medical image analysis field was analyzed through a literature review. Literature searches were conducted on PubMed, ResearchGate, Google and Cochrane Review using the key word. Through literature search, 114 abstracts were searched, and 98 abstracts were reviewed, excluding 16 duplicates. In the reviewed literature, AI is applied in classification, localization, disease detection, disease segmentation, and fit degree of registration images. In machine learning (ML), prior feature extraction and inputting the extracted feature values into the neural network have disappeared. Instead, it appears that the neural network is changing to a deep learning (DL) method with multiple hidden layers. The reason is thought to be that feature extraction is processed in the DL process due to the increase in the amount of memory of the computer, the improvement of the calculation speed, and the construction of big data. In order to apply the analysis of medical images using AI to medical care, the role of physicians is important. Physicians must be able to interpret and analyze the predictions of AI algorithms. Additional medical education and professional development for existing physicians is needed to understand AI. Also, it seems that a revised curriculum for learners in medical school is needed.
Keywords
EHR; Big-Data; Artificial Intelligence; Medical Image; Clinical Medical Decision;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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