삼성융합의과학원 - 삼성융합의과학원

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관심분야

인공지능, 의료인공지능, 소프트웨어 의료기기, 진단보조, 임상의사결정보조

학술지 논문

  • (2023)  Bone Age Assessment Using Artificial Intelligence in Korean Pediatric Population: A Comparison of Deep-Learning Models Trained With Healthy Chronological and Greulich-Pyle Ages as Labels.  KOREAN JOURNAL OF RADIOLOGY.  24,  11
  • (2023)  Uncover This Tech Term: Foundation Model.  KOREAN JOURNAL OF RADIOLOGY.  24,  10
  • (2023)  An interpretable and interactive deep learning algorithm for a clinically applicable retinal fundus diagnosis system by modelling finding-disease relationship.  SCIENTIFIC REPORTS.  13,  1

학술회의논문

  • (2023)  Improving Out-of-Distribution Detection Performance using Synthetic Outlier Exposure Generated by Visual Foundation Models.  British Machine Vision Conference.  영국
  • (2023)  Key Feature Replacement of In-Distribution Samples for Out-of-Distribution Detection.  AAAI Conference on Artificial Intelligence.  미국
  • (2022)  A Neural Pre-Conditioning Active Learning Algorithm to Reduce Label Complexity.  Conference on Neural Information Processing Systems.  미국