| 2022 | | A Deep Residual U-Net Algorithm for Automatic Detection and Quantification of Ascites on Abdominopelvic Computed Tomography Images Acquired in the Emergency Department: Model Development and Validation | 김재근, 이제희, 허지미 |
| 2024 | | Accuracy of posteroanterior cephalogram landmarks and measurements identification using a cascaded convolutional neural network algorithm: A multicenter study | 김영호 |
| 2022 | | An artificial intelligence electrocardiogram analysis for detecting cardiomyopathy in the peripartum period | 진우람 |
| 2019 | | Application of deep learning to the diagnosis of cervical lymph node metastasis from thyroid cancer with CT | 하은주 |
| 2021 | | Applications of machine learning and deep learning to thyroid imaging: Where do we stand? | 하은주 |
| 2022 | | Artificial intelligence and machine learning on diagnosis and classification of hip fracture: systematic review | 김정택 |
| 2023 | | Artificial Intelligence for Neurosurgery: Current State and Future Directions | 김상현, 노성현, 조평구 |
| 2022 | | Artificial intelligence for predicting survival following deceased donor liver transplantation: Retrospective multi-center study | 김봉완 |
| 2023 | | Artificial Intelligence in Gastric Cancer Imaging With Emphasis on Diagnostic Imaging and Body Morphometry | 허지미 |
| 2023 | | Artificial Intelligence in the Pathology of Gastric Cancer | 김석휘 |
| 2022 | | Artificial intelligence versus physicians on interpretation of printed ECG images: Diagnostic performance of ST-elevation myocardial infarction on electrocardiography | 고유라, 박민지, 소문승, 최유진 |
| 2022 | | Artificial intelligence–powered programmed death ligand 1 analyser reduces interobserver variation in tumour proportion score for non–small cell lung cancer with better prediction of immunotherapy response | 김석휘 |
| 2021 | | Automated detection of acute myocardial infarction using asynchronous electrocardiogram signals-preview of implementing artificial intelligence with multichannel electrocardiographs obtained from smartwatches: Retrospective study | 임홍석 |
| 2020 | | Clinical evaluation of atlas- and deep learning-based automatic segmentation of multiple organs and clinical target volumes for breast cancer | 정승연 |
| 2018 | | Computer-Aided Diagnosis of Thyroid Nodules via Ultrasonography: Initial Clinical Experience | 강소영, 하은주, 한미란 |
| 2019 | | Computer-aided diagnosis system for thyroid nodules on ultrasonography: diagnostic performance and reproducibility based on the experience level of operators | 김혜진, 하은주, 한미란 |
| 2020 | | Development and Validation of a Deep Learning System for Segmentation of Abdominal Muscle and Fat on Computed Tomography | 허지미 |
| 2023 | | Development of a machine learning-based fine-grained risk stratification system for thyroid nodules using predefined clinicoradiological features | 이다현, 하은주 |
| 2020 | | Discovering hidden information in biosignals from patients using artificial intelligence | 윤덕용 |
| 2023 | | Effect of Artificial Intelligence or Machine Learning on Prediction of Hip Fracture Risk: Systematic Review | 김정택 |
| 2022 | | Electrocardiographic biomarker based on machine learning for detecting overt hyperthyroidism | 박래웅, 소문승, 전자영, 진우람 |
| 2023 | | Generative Adversarial Network-Based Image Conversion Among Different Computed Tomography Protocols and Vendors: Effects on Accuracy and Variability in Quantifying Regional Disease Patterns of Interstitial Lung Disease | 선주성, 유슬기 |
| 2023 | | Prognostic artificial intelligence model to predict 5 year survival at 1 year after gastric cancer surgery based on nutrition and body morphometry | 한상욱, 허지미, 허훈 |
| 2019 | | Real-World Performance of Computer-Aided Diagnosis System for Thyroid Nodules Using Ultrasonography | 하은주, 한미란 |
