| 2020 | Machine Learning Framework to Identify Individuals at Risk of Rapid Progression of Coronary Atherosclerosis: From the PARADIGM Registry | 신상훈 | Article |
| 2023 | Machine learning models for predicting depression in Korean young employees | 김석선 | Article |
| 2022 | Machine learning models for predicting risk of depression in Korean college students: Identifying family and individual factors | 김석선 | Article |
| 2021 | Machine Learning-Based Automatic Classification of Video Recorded Neonatal Manipulations and Associated Physiological Parameters: A Feasibility Study | 조수진 | Article |
| 2018 | Machine Learning-Based Fast Angular Prediction Mode Decision Technique in Video Coding | 강제원 | Article |
| 2022 | On the Confidence of Stereo Matching in a Deep-Learning Era: A Quantitative Evaluation | 민동보 | Article |
| 2022 | Predicting preterm birth through vaginal microbiota, cervical length, and WBC using a machine learning model | 김영주; 유영아; Ansari Abuzar; 박선화 | Article |
| 2023 | Predicting the Risk of Sleep Disorders Using a Machine Learning-Based Simple Questionnaire: Development and Validation Study | 김지현 | Article |
| 2022 | Prediction of Emergency Cesarean Section Using Machine Learning Methods: Development and External Validation of a Nationwide Multicenter Dataset in Republic of Korea | 박미혜 | Article |
| 2023 | Prediction of medication-related osteonecrosis of the jaws using machine learning methods from estrogen receptor 1 polymorphisms and clinical information | 곽혜선; 김선종; 김진우; 이정 | Article |
| 2023 | Reduction of False Positives for Runtime Errors in C/C++ Software: A Comparative Study | 최병주; 박지현 | Article |
| 2019 | Retrieval of Total Precipitable Water from Himawari-8 AHI Data: A Comparison of Random Forest, Extreme Gradient Boosting, and Deep Neural Network | 안명환 | Article |
| 2023 | Risk factors based vessel-specific prediction for stages of coronary artery disease using Bayesian quantile regression machine learning method: Results from the PARADIGM registry | 신상훈 | Article |
| 2022 | Risk Scoring System for Vancomycin-Associated Acute Kidney Injury | 곽혜선; 이정 | Article |
| 2022 | ShellCore: Automating Malicious IoT Software Detection Using Shell Commands Representation | 양대헌 | Article |
| 2019 | The Machine Learning-Based Dropout Early Warning System for Improving the Performance of Dropout Prediction | 정제영; 이선복 | Article |
| 2020 | Twitter Analysis of the Nonmedical Use and Side Effects of Methylphenidate: Machine Learning Study | 김명규 | Article |
