Early prediction of need for invasive mechanical ventilation in the neonatal intensive care unit using artificial intelligence and electronic health records: a clinical study
Kim, Younga, Kim, Hyeongsub, Choi, Jaewoo, Cho, Kyungjae, Yoo, Dongjoon, Lee, Yeha, Park, Su Jeong, Jeong, Mun Hui, Jeong, Seong Hee, Park, Kyung Hee, Byun, Shin-Yun, Kim, Taehwa, Ahn, Sung-Ho, Cho, Woo Hyun, Lee, Narae
Published in BMC pediatrics (23.10.2023)
Published in BMC pediatrics (23.10.2023)
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Development and Validation of Deep-Learning-Based Sepsis and Septic Shock Early Prediction System (DeepSEPS) Using Real-World ICU Data
Kim, Taehwa, Tae, Yunwon, Yeo, Hye Ju, Jang, Jin Ho, Cho, Kyungjae, Yoo, Dongjoon, Lee, Yeha, Ahn, Sung-Ho, Kim, Younga, Lee, Narae, Cho, Woo Hyun
Published in Journal of clinical medicine (01.11.2023)
Published in Journal of clinical medicine (01.11.2023)
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Real-time machine learning model to predict short-term mortality in critically ill patients: development and international validation
Lim, Leerang, Gim, Ukdong, Cho, Kyungjae, Yoo, Dongjoon, Ryu, Ho Geol, Lee, Hyung-Chul
Published in Critical care (London, England) (14.03.2024)
Published in Critical care (London, England) (14.03.2024)
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Improving the Performance of a Neural Network for Early Prediction of Sepsis
Lee, ByeongTak, Cho, KyungJae, Kwon, Oyeon, Lee, Yeha
Published in 2019 Computing in Cardiology (CinC) (01.09.2019)
Published in 2019 Computing in Cardiology (CinC) (01.09.2019)
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