Machine learning model for predicting acute kidney injury progression in critically ill patients

被引:0
|
作者
Canzheng Wei
Lifan Zhang
Yunxia Feng
Aijia Ma
Yan Kang
机构
[1] West China Hospital of Sichuan University,Department of Critical Care Medicine
[2] West China Hospital of Sichuan University,Department of Gastroenterology
[3] University of Electronic Science and Technology of China,Department of Nephrology, Mianyan Central Hospital
关键词
Acute kidney injury; Critical care; Logistic Models; Extreme gradient boosting;
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
相关论文
共 50 条
  • [1] Machine learning model for predicting acute kidney injury progression in critically ill patients
    Wei, Canzheng
    Zhang, Lifan
    Feng, Yunxia
    Ma, Aijia
    Kang, Yan
    [J]. BMC MEDICAL INFORMATICS AND DECISION MAKING, 2022, 22 (01)
  • [2] Interpretable machine learning model for predicting acute kidney injury in critically ill patients
    Li, Xunliang
    Wang, Peng
    Zhu, Yuke
    Zhao, Wenman
    Pan, Haifeng
    Wang, Deguang
    [J]. BMC MEDICAL INFORMATICS AND DECISION MAKING, 2024, 24 (01)
  • [3] Predicting outcomes of acute kidney injury in critically ill patients using machine learning
    Fateme Nateghi Haredasht
    Liesbeth Viaene
    Hans Pottel
    Wouter De Corte
    Celine Vens
    [J]. Scientific Reports, 13
  • [4] Predicting outcomes of acute kidney injury in critically ill patients using machine learning
    Nateghi Haredasht, Fateme
    Viaene, Liesbeth
    Pottel, Hans
    De Corte, Wouter
    Vens, Celine
    [J]. SCIENTIFIC REPORTS, 2023, 13 (01)
  • [5] Federated machine learning for predicting acute kidney injury in critically ill patients: a multicenter study in Taiwan
    Huang, Chun-Te
    Wang, Tsai-Jung
    Kuo, Li-Kuo
    Tsai, Ming-Ju
    Cia, Cong-Tat
    Chiang, Dung-Hung
    Chang, Po-Jen
    Chong, Inn-Wen
    Tsai, Yi-Shan
    Chu, Yuan-Chia
    Liu, Chia-Jen
    Chen, Cheng-Hsu
    Pai, Kai-Chih
    Wu, Chieh-Liang
    [J]. HEALTH INFORMATION SCIENCE AND SYSTEMS, 2023, 11 (01)
  • [6] Federated machine learning for predicting acute kidney injury in critically ill patients: a multicenter study in Taiwan
    Chun-Te Huang
    Tsai-Jung Wang
    Li-Kuo Kuo
    Ming-Ju Tsai
    Cong-Tat Cia
    Dung-Hung Chiang
    Po-Jen Chang
    Inn-Wen Chong
    Yi-Shan Tsai
    Yuan-Chia Chu
    Chia-Jen Liu
    Cheng-Hsu Chen
    Kai-Chih Pai
    Chieh-Liang Wu
    [J]. Health Information Science and Systems, 11
  • [7] Predicting acute kidney injury in critically ill patients using comorbid conditions utilizing machine learning
    Shawwa, Khaled
    Ghosh, Erina
    Lanius, Stephanie
    Schwager, Emma
    Eshelman, Larry
    Kashani, Kianoush B.
    [J]. CLINICAL KIDNEY JOURNAL, 2021, 14 (05) : 1428 - 1435
  • [8] Machine Learning Models for Predicting Mortality in Critically Ill Patients with Sepsis-Associated Acute Kidney Injury: A Systematic Review
    Wu, Chieh-Chen
    Poly, Tahmina Nasrin
    Weng, Yung-Ching
    Lin, Ming-Chin
    Islam, Md. Mohaimenul
    [J]. DIAGNOSTICS, 2024, 14 (15)
  • [9] Acute kidney injury in critically ill patients
    Bouzas-Mosquera, Alberto
    Vazquez-Rodriguez, Jose M.
    Peteiro, Jesus
    [J]. CRITICAL CARE MEDICINE, 2009, 37 (01) : 377 - 377
  • [10] Machine-learning model for predicting oliguria in critically ill patients
    Yasuo Yamao
    Takehiko Oami
    Jun Yamabe
    Nozomi Takahashi
    Taka-aki Nakada
    [J]. Scientific Reports, 14