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IEEE Transactions on Neural Networks and Learning Systems|March 31, 2022
Tackling the Challenges in Scene Graph Generation With Local-to-Global InteractionsSangmin Woo, Junhyug Noh, Kangil KimScientific Reports|August 23, 2017
A Machine Learning Approach Using Survival Statistics to Predict Graft Survival in Kidney Transplant Recipients: A Multicenter Cohort StudyKyung Don Yoo, Junhyug Noh, Hajeong Lee, et al.Kidney Research and Clinical Practice|February 20, 2025
A novel approach to the relation of multi-pollutant effect and kidney dysfunction: data analysis from the Korean National Environmental Health Survey Cycle 3 (2015-2017)Inae Lee, Junhyug Noh, Yaerim Kim, et al.Scientific Reports|August 15, 2020
Recalibration and validation of the Charlson Comorbidity Index in an Asian population: the National Health Insurance Service-National Sample Cohort studyJae Shin Choi, Myoung-Hee Kim, Yong Chul Kim, et al.Scientific Reports|November 28, 2024
Predicting early mortality in hemodialysis patients: a deep learning approach using a nationwide prospective cohort in South KoreaJunhyug Noh, Sun Young Park, Wonho Bae, et al.Scientific Reports|May 6, 2020
Prediction of the Mortality Risk in Peritoneal Dialysis Patients using Machine Learning Models: A Nation-wide Prospective Cohort in KoreaJunhyug Noh, Kyung Don Yoo, Wonho Bae, et al.Scientific Reports|March 22, 2023
Predicting outcomes of continuous renal replacement therapy using body composition monitoring: a deep-learning approachKyung Don Yoo, Junhyug Noh, Wonho Bae, et al.Medicine|August 19, 2016
Superior outcomes of kidney transplantation compared with dialysis: An optimal matched analysis of a national population-based cohort study between 2005 and 2008 in KoreaKyung Don Yoo, Clara Tammy Kim, Myoung-Hee Kim, et al.Kidney Research and Clinical Practice|September 4, 2025
Development of a prediction tool for kidney function decline in children with chronic kidney diseaseSangwoo Moon, Junhyug Noh, Hee Gyung Kang, et al.Pageof 1