| 2023 | | A Deep Learning-Based Automatic Collateral Assessment in Patients with Acute Ischemic Stroke | 이진수, 홍지만 |
| 2022 | | An artificial intelligence electrocardiogram analysis for detecting cardiomyopathy in the peripartum period | 진우람 |
| 2020 | | Application of deep learning to the diagnosis of cervical lymph node metastasis from thyroid cancer with CT: external validation and clinical utility for resident training | 하은주 |
| 2023 | | Artificial Intelligence in Gastric Cancer Imaging With Emphasis on Diagnostic Imaging and Body Morphometry | 허지미 |
| 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 |
| 2024 | | Assessment of deep learning-based auto-contouring on interobserver consistency in target volume and organs-at-risk delineation for breast cancer: Implications for RTQA program in a multi-institutional study | 조오연 |
| 2021 | | Automated assessment of the substantia nigra on susceptibility map-weighted imaging using deep convolutional neural networks for diagnosis of Idiopathic Parkinson's disease | 윤정한 |
| 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 |
| 2021 | | Clinical feasibility of deep learning-based auto-segmentation of target volumes and organs-at-risk in breast cancer patients after breast-conserving surgery | 정승연 |
| 2023 | | Deep Interactive Learning-based ovarian cancer segmentation of H&E-stained whole slide images to study morphological patterns of BRCA mutation | 노진 |
| 2023 | | Deep learning referral suggestion and tumour discrimination using explainable artificial intelligence applied to multiparametric MRI | 이다현 |
| 2024 | | Deep learning-based fully automatic Risser stage assessment model using abdominal radiographs | 황지선 |
| 2024 | | Deep learning-based metastasis detection in patients with lung cancer to enhance reproducibility and reduce workload in brain metastasis screening with MRI: a multi-center study | 이다현 |
| 2020 | | Development and Validation of a Deep Learning System for Segmentation of Abdominal Muscle and Fat on Computed Tomography | 허지미 |
| 2024 | | Development of a multi-modal learning-based lymph node metastasis prediction model for lung cancer | 김철호, 유슬기, 허재성 |
| 2020 | | Discovering hidden information in biosignals from patients using artificial intelligence | 윤덕용 |
| 2022 | | Electrocardiographic biomarker based on machine learning for detecting overt hyperthyroidism | 박래웅, 소문승, 전자영, 진우람 |
| 2024 | | Hyperosmolar therapy response in traumatic brain injury: Explainable artificial intelligence based long-term time series forecasting approach | 김세혁, 노태훈, 유남규 |
| 2023 | | Orthognathic surgical planning using graph CNN with dual embedding module: External validations with multi-hospital datasets | 김영호 |
| 2022 | | Prediction of Decompensation and Death in Advanced Chronic Liver Disease Using Deep Learning Analysis of Gadoxetic Acid-Enhanced MRI | 허수빈 |
| 2023 | | The diagnostic performance and clinical value of deep learning-based nodule detection system concerning influence of location of pulmonary nodule | 박범희, 선주성, 유슬기, 윤재성, 하태양 |
