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Sungjun Hong

Showing results (1-10 of 34) with videos related to

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Studies in Health Technology and Informatics|May 17, 2025
Improving CPR Predictive Model in ED: The Role of Initial Data and KTASSungsoo Hong, Heejung Hyun, Sungjun Hong
Studies in Health Technology and Informatics|May 17, 2025
Clustering Voice of the Customer Insights: Identifying Key Needs for AI-Based Early Warning SystemHyunwoo Choo, Heejung Hyun, Sungjun Hong
Inorganic Chemistry|May 12, 2009
Intermediates in reactions of copper(I) complexes with N-oxides: from the formation of stable adducts to oxo transferSungjun Hong, Aalo K Gupta, William B Tolman
Sensors (Basel, Switzerland)|August 11, 2017
Efficient Pedestrian Detection at Nighttime Using a Thermal CameraJeonghyun Baek, Sungjun Hong, Jisu Kim, et al.
JMIR Medical Informatics|March 28, 2020
Predicting Adverse Outcomes for Febrile Patients in the Emergency Department Using Sparse Laboratory Data: Development of a Time Adaptive ModelSungjoo Lee, Sungjun Hong, Won Chul Cha, et al.
JMIR Medical Informatics|August 5, 2020
Prediction of Cardiac Arrest in the Emergency Department Based on Machine Learning and Sequential Characteristics: Model Development and Retrospective Clinical Validation StudySungjun Hong, Sungjoo Lee, Jeonghoon Lee, et al.
Studies in Health Technology and Informatics|August 8, 2025
Development and Validation of Pneumonia Patients Prognosis Prediction Model in Emergency Department Disposition TimeSunjin Hwang, Sejin Heo, Sungjun Hong, et al.
Journal of the American Chemical Society|October 26, 2007
Copper(I)-alpha-ketocarboxylate complexes: characterization and O2 reactions that yield copper-oxygen intermediates capable of hydroxylating arenesSungjun Hong, Stefan M Huber, Laura Gagliardi, et al.
Scientific Reports|November 26, 2024
Development of a flexible feature selection framework in radiomics-based prediction modeling: Assessment with four real-world datasetsSungsoo Hong, Sungjun Hong, Eunsun Oh, et al.
Scientific Reports|March 2, 2026
Multimodal AI-based 28-day mortality prediction of pneumonia patients at ED discharge: a multicenter studySunjin Hwang, Sejin Heo, Sungjun Hong, et al.
Pageof 4

Showing results (1-10 of 34) with videos related to

Sort By:
Pageof 4
Studies in Health Technology and Informatics|May 17, 2025
Improving CPR Predictive Model in ED: The Role of Initial Data and KTASSungsoo Hong, Heejung Hyun, Sungjun Hong
Studies in Health Technology and Informatics|May 17, 2025
Clustering Voice of the Customer Insights: Identifying Key Needs for AI-Based Early Warning SystemHyunwoo Choo, Heejung Hyun, Sungjun Hong
Inorganic Chemistry|May 12, 2009
Intermediates in reactions of copper(I) complexes with N-oxides: from the formation of stable adducts to oxo transferSungjun Hong, Aalo K Gupta, William B Tolman
Sensors (Basel, Switzerland)|August 11, 2017
Efficient Pedestrian Detection at Nighttime Using a Thermal CameraJeonghyun Baek, Sungjun Hong, Jisu Kim, et al.
JMIR Medical Informatics|March 28, 2020
Predicting Adverse Outcomes for Febrile Patients in the Emergency Department Using Sparse Laboratory Data: Development of a Time Adaptive ModelSungjoo Lee, Sungjun Hong, Won Chul Cha, et al.
JMIR Medical Informatics|August 5, 2020
Prediction of Cardiac Arrest in the Emergency Department Based on Machine Learning and Sequential Characteristics: Model Development and Retrospective Clinical Validation StudySungjun Hong, Sungjoo Lee, Jeonghoon Lee, et al.
Studies in Health Technology and Informatics|August 8, 2025
Development and Validation of Pneumonia Patients Prognosis Prediction Model in Emergency Department Disposition TimeSunjin Hwang, Sejin Heo, Sungjun Hong, et al.
Journal of the American Chemical Society|October 26, 2007
Copper(I)-alpha-ketocarboxylate complexes: characterization and O2 reactions that yield copper-oxygen intermediates capable of hydroxylating arenesSungjun Hong, Stefan M Huber, Laura Gagliardi, et al.
Scientific Reports|November 26, 2024
Development of a flexible feature selection framework in radiomics-based prediction modeling: Assessment with four real-world datasetsSungsoo Hong, Sungjun Hong, Eunsun Oh, et al.
Scientific Reports|March 2, 2026
Multimodal AI-based 28-day mortality prediction of pneumonia patients at ED discharge: a multicenter studySunjin Hwang, Sejin Heo, Sungjun Hong, et al.
Pageof 4