Samsung Advanced Institute for Health Sciences and Technology (SAIHST) - Samsung Advanced Institute for Health Sciences and Technology (SAIHST)

  • Assistant Professor
  • JUNG, KYUHWAN

Research Interest

Artificial Intelligence, Medical Artificial Intelligence, Software as a Medical Device, Computer-aided Diagnosis, Computer-aided Decision Support System

Journal Articles

  • (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

Conference Paper

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