2024 | | Predicted brain age (PBA), promising surrogate indicator for neurodevelopment in preterm baby: how to predict accurately? | 한미란 |
2015 | | Predicted EC₅₀ and EC₉₅ of Remifentanil for Smooth Removal of a Laryngeal Mask Airway Under Propofol Anesthesia. | 김종엽, 유지영 |
2007 | | Predicted Effect-site Concentration of Remifentanil for Facilitating Laryngeal Mask Airway Insertion with Propofol Target-Controlled Infusion | 김종엽, 김진수, 문봉기, 박성용 |
2018 | | Predicting effective remifentanil concentration in 95% of patients to prevent emergence cough after laryngomicroscopic surgery | 김종엽, 김하연, 이숙영 |
2020 | | Predicting Endovascular Treatment Outcomes in Acute Vertebrobasilar Artery Occlusion: A Model to Aid Patient Selection from the ASIAN KR Registry | 박범희, 이성준, 이진수, 홍지만 |
2010 | | Predicting factors of unexpected peritoneal seeding in locally advanced gastric cancer: indications for staging laparoscopy. | 허훈 |
2023 | | Predicting Mechanical Complications After Adult Spinal Deformity Operation Using a Machine Learning Based on Modified Global Alignment and Proportion Scoring With Body Mass Index and Bone Mineral Density | 김상현, 노성현 |
2016 | | Predicting Model of Lymph Node Metastasis Using Preoperative Tumor Grade, Transvaginal Ultrasound, and Serum CA-125 Level in Patients With Endometrial Cancer | 공태욱, 백지흠, 유희석, 이지선, 장석준 |
2022 | | Predicting Mortality of Korean Geriatric Trauma Patients: A Comparison between Geriatric Trauma Outcome Score and Trauma and Injury Severity Score | 박지예, 이윤환 |
2020 | | Predicting Old-age Mortality Using Principal Component Analysis: Results from a National Panel Survey in Korea | 신재용 |
2023 | | Predicting physical activity and sarcopenia-related health outcomes in women with rheumatoid arthritis: A test of the self-determination theory | 김춘자, 정주양 |
2024 | | Predicting responses to omalizumab in antihistamine-refractory chronic urticaria: A real-world longitudinal study | 남동호, 박해심, 신유섭, 예영민, 이영수, 장재혁 |
2021 | | Predicting speech discrimination scores from pure-tone thresholds—A machine learning-based approach using data from 12,697 subjects | 김한태, 장정훈, 정연훈 |
2023 | | Predicting Survival Outcomes in Post-Cardiac Arrest Syndrome: The Impact of Combined Sequential Organ Failure Assessment Score and Serum Lactate Measurement | 김혁훈, 양희원, 이방실 |
2020 | | Predicting survival using the 2016 World Health Organization classification for anaplastic glioma | 노태훈 |
2024 | | Predicting the Outcome of Pediatric Oral Food Challenges for Determining Tolerance Development | 정경욱 |
2014 | | Predicting type 2 diabetes using Sasang constitutional medicine. | 조남한 |
2014 | | Prediction for TNF Inhibitor Users in RA Patients According to Reimbursement Criteria Based on DAS28 | 김현아, 서창희 |
2022 | | Prediction Model for 30-Day Mortality after Non-Cardiac Surgery Using Machine-Learning Techniques Based on Preoperative Evaluation of Electronic Medical Records | 김하연, 박래웅 |
2023 | | Prediction model for postoperative atrial fibrillation in non-cardiac surgery using machine learning | 김하연 |