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Guilan Kong

Showing results (1-10 of 38) with videos related to

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Health Informatics Journal|October 11, 2014
Protecting privacy in a clinical data warehouseGuilan Kong, Zhichun Xiao
Kidney Medicine|January 6, 2025
Acute Kidney Injury Prognosis Prediction Using Machine Learning Methods: A Systematic ReviewYu Lin, Tongyue Shi, Guilan Kong
International Journal of Medical Informatics|March 28, 2019
Predicting in-hospital mortality of patients with acute kidney injury in the ICU using random forest modelKe Lin, Yonghua Hu, Guilan Kong
BMC Medical Informatics and Decision Making|October 3, 2020
Using machine learning methods to predict in-hospital mortality of sepsis patients in the ICUGuilan Kong, Ke Lin, Yonghua Hu
IEEE Journal of Biomedical and Health Informatics|January 20, 2026
Subphenotype Identification for Sepsis-Associated Acute Kidney Injury Using Graph Bidirectional Mamba NetworksHaowei Xu, Wentie Liu, Tongyue Shi, et al.
JAMIA Open|July 7, 2025
Artificial intelligence models for predicting acute kidney injury in the intensive care unit: a systematic review of modeling methods, data utilization, and clinical applicabilityTongyue Shi, Yu Lin, Huiying Zhao, et al.
Health Data Science|August 6, 2024
ERTool: A Python Package for Efficient Implementation of the Evidential Reasoning Approach for Multi-Source Evidence FusionTongyue Shi, Liya Guo, Zeyuan Shen, et al.
Journal of Affective Disorders|January 17, 2022
Bidirectional associations of vision loss, hearing loss, and dual sensory loss with depressive symptoms among the middle-aged and older adults in ChinaWenwen Liu, Chao Yang, Lili Liu, et al.
AMIA ... Annual Symposium Proceedings. AMIA Symposium|February 23, 2026
AKI-Detector: A Multi-Agent Framework by Integrating Machine Learning and Large Language Models for Early Prediction of Acute Kidney Injury in ICUTongyue Shi, Meirong Xiao, Haowei Xu, et al.
The International Journal of Social Psychiatry|June 7, 2024
Association of the intergenerational structure with the onset of depressive symptoms among middle-aged and older adults in ChinaJun Ma, Wenwen Liu, Yangfan Chai, et al.
Pageof 4

Showing results (1-10 of 38) with videos related to

Sort By:
Pageof 4
Health Informatics Journal|October 11, 2014
Protecting privacy in a clinical data warehouseGuilan Kong, Zhichun Xiao
Kidney Medicine|January 6, 2025
Acute Kidney Injury Prognosis Prediction Using Machine Learning Methods: A Systematic ReviewYu Lin, Tongyue Shi, Guilan Kong
International Journal of Medical Informatics|March 28, 2019
Predicting in-hospital mortality of patients with acute kidney injury in the ICU using random forest modelKe Lin, Yonghua Hu, Guilan Kong
BMC Medical Informatics and Decision Making|October 3, 2020
Using machine learning methods to predict in-hospital mortality of sepsis patients in the ICUGuilan Kong, Ke Lin, Yonghua Hu
IEEE Journal of Biomedical and Health Informatics|January 20, 2026
Subphenotype Identification for Sepsis-Associated Acute Kidney Injury Using Graph Bidirectional Mamba NetworksHaowei Xu, Wentie Liu, Tongyue Shi, et al.
JAMIA Open|July 7, 2025
Artificial intelligence models for predicting acute kidney injury in the intensive care unit: a systematic review of modeling methods, data utilization, and clinical applicabilityTongyue Shi, Yu Lin, Huiying Zhao, et al.
Health Data Science|August 6, 2024
ERTool: A Python Package for Efficient Implementation of the Evidential Reasoning Approach for Multi-Source Evidence FusionTongyue Shi, Liya Guo, Zeyuan Shen, et al.
Journal of Affective Disorders|January 17, 2022
Bidirectional associations of vision loss, hearing loss, and dual sensory loss with depressive symptoms among the middle-aged and older adults in ChinaWenwen Liu, Chao Yang, Lili Liu, et al.
AMIA ... Annual Symposium Proceedings. AMIA Symposium|February 23, 2026
AKI-Detector: A Multi-Agent Framework by Integrating Machine Learning and Large Language Models for Early Prediction of Acute Kidney Injury in ICUTongyue Shi, Meirong Xiao, Haowei Xu, et al.
The International Journal of Social Psychiatry|June 7, 2024
Association of the intergenerational structure with the onset of depressive symptoms among middle-aged and older adults in ChinaJun Ma, Wenwen Liu, Yangfan Chai, et al.
Pageof 4