Published on in Vol 23, No 8 (2021): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/23508, first published .
Development and Validation of Unplanned Extubation Prediction Models Using Intensive Care Unit Data: Retrospective, Comparative, Machine Learning Study

Development and Validation of Unplanned Extubation Prediction Models Using Intensive Care Unit Data: Retrospective, Comparative, Machine Learning Study

Development and Validation of Unplanned Extubation Prediction Models Using Intensive Care Unit Data: Retrospective, Comparative, Machine Learning Study

Journals

  1. Campagner A, Sternini F, Cabitza F. Decisions are not all equal—Introducing a utility metric based on case-wise raters’ perceptions. Computer Methods and Programs in Biomedicine 2022;221:106930 View
  2. Huang H, Yu S, Zheng J, Tian L. The Clinical Nursing Pathway on Prevention of Catheter Slippage with Intensive Care Unit Patients: A Systematic Review and Meta-Analysis. Evidence-Based Complementary and Alternative Medicine 2022;2022:1 View
  3. Liu K, Liu Z, Li L, Zhang M, Deng X, Zhu H. Predictive value of the unplanned extubation risk assessment scale in hospitalized patients with tubes. World Journal of Clinical Cases 2022;10(36):13274 View
  4. Perry-Eaddy M, Braccialarghe K, Cowl A, Melendez E. Can an unplanned extubation checklist solely identify children at-risk for adverse events? A response to the pediatric unplanned extubation risk score. Heart & Lung 2023;62:278 View
  5. Muñoz-Bonet J, Posadas-Blázquez V, González-Galindo L, Sánchez-Zahonero J, Vázquez-Martínez J, Castillo A, Brines J. Exploring the clinical relevance of vital signs statistical calculations from a new-generation clinical information system. Scientific Reports 2023;13(1) View
  6. Ma H, Pan H, Dong X, Li L. An Empirical Study of Feedforward Control in Unplanned Extubation of Nasogastric Tube. Journal of Multidisciplinary Healthcare 2023;Volume 16:1465 View
  7. Zhang J, Ma G, Peng S, Hou J, Xu R, Luo L, Hu J, Yao N, Wang J, Huang X. Risk Factors and Predictive Models for Peripherally Inserted Central Catheter Unplanned Extubation in Patients With Cancer: Prospective, Machine Learning Study. Journal of Medical Internet Research 2023;25:e49016 View
  8. Su L, Liu S, Long Y, Chen C, Chen K, Chen M, Chen Y, Cheng Y, Cui Y, Ding Q, Ding R, Duan M, Gao T, Gu X, He H, He J, Hu B, Hu C, Huang R, Huang X, Jiang H, Jiang J, Lan Y, Li J, Li L, Li L, Li W, Li Y, Lin J, Luo X, Lyu F, Mao Z, Miao H, Shang X, Shang X, Shang Y, Shen Y, Shi Y, Sun Q, Sun W, Tang Z, Wang B, Wang H, Wang H, Wang L, Wang L, Wang S, Wang Z, Wang Z, Wei D, Wu J, Wu Q, Xing X, Yang J, Yang X, Yu J, Yu W, Yu Y, Yuan H, Zhai Q, Zhang H, Zhang L, Zhang M, Zhang Z, Zhao C, Zheng R, Zhong L, Zhou F, Zhu W. Chinese experts’ consensus on the application of intensive care big data. Frontiers in Medicine 2024;10 View
  9. Xu X, Shen L, Qu Y, Li D, Zhao X, Wei H, Yue S. Experimental validation and comprehensive analysis of m6A methylation regulators in intervertebral disc degeneration subpopulation classification. Scientific Reports 2024;14(1) View
  10. Barea Mendoza J, Valiente Fernandez M, Pardo Fernandez A, Gómez Álvarez J. Perspectivas actuales sobre el uso de la inteligencia artificial en la seguridad del paciente crítico. Medicina Intensiva 2024 View
  11. Barea Mendoza J, Valiente Fernandez M, Pardo Fernandez A, Gómez Álvarez J. Current perspectives on the use of artificial intelligence in critical patient safety. Medicina Intensiva (English Edition) 2024 View
  12. Wu J, Xiao Z, Chen S, Huang B, Han S, Huang H. Development of an evidence‐based nursing practice program for preventing unplanned endotracheal extubations in the intensive care unit: A Delphi method study. Journal of Clinical Nursing 2024 View