Effect of Deep Learning-Based Artificial Intelligence on Radiologists' Performance in Identifying Nigrosome 1 Abnormalities on Susceptibility Map-Weighted Imaging.
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| Title: | Effect of Deep Learning-Based Artificial Intelligence on Radiologists' Performance in Identifying Nigrosome 1 Abnormalities on Susceptibility Map-Weighted Imaging. |
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| Authors: | Park J; Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea., Lim CY; Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea., Won SY; Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea., Na HK; Department of Neurology, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea., Lee PH; Department of Neurology, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea., Baek SY; Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.; Research Institute for Future Medicine, Samsung Medical Center, Seoul, Republic of Korea., Roh YH; Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea., Seong M; Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea., Sim Y; Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea., Kim EY; Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea., Kim ST; Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea., Sohn B; Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea. beomseoksohn@gmail.com. |
| Source: | Korean journal of radiology [Korean J Radiol] 2025 Aug; Vol. 26 (8), pp. 771-781. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Korean Society of Radiology Country of Publication: Korea (South) NLM ID: 100956096 Publication Model: Print Cited Medium: Internet ISSN: 2005-8330 (Electronic) Linking ISSN: 12296929 NLM ISO Abbreviation: Korean J Radiol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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