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전체 가 나 다 라 마 바 사 아 자 차 카 타 파 하

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Conference
Comparison of self-supervised learning methods for optical coherence tomography image classification
  • Shim, Sungho ; 
  • Yang, Hyun-Lim ; 
  • Kim, Min-Soo
  • 2024-05
  • Shim, Sungho. (2024-05). Comparison of self-supervised learning methods for optical coherence tomography image classification. 8th International Conference on Medical and Health Informatics, ICMHI 2024, 41–46. doi: 10.1145/3673971.3673989
  • Association for Computing Machinery
  • View : 53
  • Download : 0

Development and validation of a multi-stage self-supervised learning model for optical coherence tomography image classification

Article
Development and validation of a multi-stage self-supervised learning model for optical coherence tomography image classification
  • Shim, Sungho ; 
  • Kim, Min-Soo ; 
  • Yae, Che Gyem ; 
  • Kang, Yong Koo ; 
  • Do, Jae Rock ; 
  • Kim, Hong Kyun ; 
  • Yang, Hyun-Lim
  • 2025-05
  • Journal of the American Medical Informatics Association : JAMIA, v.32, no.5, pp.800 - 810
  • Oxford University Press
  • View : 65
  • Download : 8

Development and Validation of an Arterial Pressure-Based Cardiac Output Algorithm Using a Convolutional Neural Network: Retrospective Study Based on Prospective Registry Data

Article
Development and Validation of an Arterial Pressure-Based Cardiac Output Algorithm Using a Convolutional Neural Network: Retrospective Study Based on Prospective Registry Data
  • Yang, Hyun-Lim ; 
  • Jung, Chul-Woo ; 
  • Yang, Seong Mi ; 
  • Kim, Min-Soo ; 
  • Shim, Sungho ; 
  • Lee, Kook Hyun ; 
  • Lee, Hyung-Chul
  • 2021-08
  • Yang, Hyun-Lim. (2021-08). Development and Validation of an Arterial Pressure-Based Cardiac Output Algorithm Using a Convolutional Neural Network: Retrospective Study Based on Prospective Registry Data. JMIR Medical Informatics, 9(8). doi: 10.2196/24762
  • JMIR Publications
  • View : 434
  • Download : 81
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