| 2024 | | A De-Identification Model for Korean Clinical Notes: Using Deep Learning Models | 박래웅 |
| 2023 | | A Deep Learning-Based Automatic Collateral Assessment in Patients with Acute Ischemic Stroke | 이진수, 홍지만 |
| 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 |
| 2020 | | Analysis of Adverse Drug Reactions Identified in Nursing Notes Using Reinforcement Learning | 박래웅 |
| 2019 | | Application of deep learning to the diagnosis of cervical lymph node metastasis from thyroid cancer with CT | 하은주 |
| 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 |
| 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 |
| 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 | 황지선 |
| 2020 | | Clinical evaluation of atlas- and deep learning-based automatic segmentation of multiple organs and clinical target volumes for breast cancer | 정승연 |
| 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 |
| 2024 | | Clinical Feasibility of Deep Learning–Based Attenuation Correction Models for Tl-201 Myocardial Perfusion SPECT | 박용진, 안영실, 윤준기, 이수진 |
| 2022 | | Content-based Image Retrieval by Using Deep Learning for Interstitial Lung Disease Diagnosis with Chest CT | 이영수 |
| 2020 | | Deep Learning Approach for Imputation of Missing Values in Actigraphy Data: Algorithm Development Study | 김은영, 노현웅, 손상준, 윤덕용, 홍창형 |
| 2021 | | Deep learning for anatomical interpretation of video bronchoscopy images | 강세윤, 박성용, 유지영 |
| 2022 | | Deep learning model for tongue cancer diagnosis using endoscopic images | 김철호, 신유섭, 장전엽, 허재성 |
| 2023 | | Deep learning referral suggestion and tumour discrimination using explainable artificial intelligence applied to multiparametric MRI | 이다현 |
| 2023 | | Deep learning using computed tomography to identify high-risk patients for acute small bowel obstruction: development and validation of a prediction model : a retrospective cohort study | 손상용, 송정호, 신호정, 한상욱, 허훈 |
| 2024 | | Deep learning-based analysis of EGFR mutation prevalence in lung adenocarcinoma H&E whole slide images | 노진, 허재성 |
| 2023 | | Deep Learning-Based Automatic Detection and Grading of Motion-Related Artifacts on Gadoxetic Acid-Enhanced Liver MRI | 허지미 |
| 2019 | | Deep Learning-Based Electrocardiogram Signal Noise Detection and Screening Model | 윤덕용, 임홍석, 정경원 |
| 2024 | | Deep learning-based fully automatic Risser stage assessment model using abdominal radiographs | 황지선 |
| 2023 | | Deep learning-based image reconstruction improves radiologic evaluation of pituitary axis and cavernous sinus invasion in pituitary adenoma | 이다현 |
| 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 |
| 2024 | | Deep learning–radiomics integrated noninvasive detection of epidermal growth factor receptor mutations in non-small cell lung cancer patients | 김철호, 노진, 유슬기, 허재성 |
| 2020 | | Development and Validation of a Deep Learning System for Segmentation of Abdominal Muscle and Fat on Computed Tomography | 허지미 |
| 2021 | | Development of a predictive model for adverse drug reactions using unstructured nursing records | 박래웅, 박호준 |
| 2020 | | Discovering hidden information in biosignals from patients using artificial intelligence | 윤덕용 |
| 2021 | | Effectiveness of transfer learning for deep learning-based electrocardiogram analysis | 윤덕용 |
| 2021 | | Evaluation of deep learning-based autosegmentation in breast cancer radiotherapy | 정승연 |
| 2023 | | Feasibility Study of Federated Learning on the Distributed Research Network of OMOP Common Data Model | 박래웅 |
| 2024 | | Optimization of vision transformer-based detection of lung diseases from chest X-ray images | 우현구 |
| 2019 | | Prediction of cognitive impairment via deep learning trained with multi-center neuropsychological test data | 문소영 |
| 2022 | | Prediction of Decompensation and Death in Advanced Chronic Liver Disease Using Deep Learning Analysis of Gadoxetic Acid-Enhanced MRI | 허수빈 |
| 2023 | | Prediction of the number of asthma patients using environmental factors based on deep learning algorithms | 박해심, 장재혁 |
| 2022 | | Radiation Dose Reduction in Digital Mammography by Deep-Learning Algorithm Image Reconstruction: A Preliminary Study | 김태희 |
| 2024 | | SEP-AlgPro: An efficient allergen prediction tool utilizing traditional machine learning and deep learning techniques with protein language model features | Basith, Shaherin, 이광 |
| 2022 | | Strategy for Improving Generalizability of Medical Imaging Artificial Intelligence Model | 박래웅, 신서정 |
| 2021 | | Style transfer strategy for developing a generalizable deep learning application in digital pathology | 노진, 박래웅 |
