Predicting Readiness to Liberate from Mechanical Ventilation Using Machine Learning: Development and Retrospective Validation

被引：0
|
作者：
Tandon, P. [1 ]
Cheng, F. [2 ]
Cheetirala, S. N. [2 ]
Parchure, P. [2 ]
Levin, M. [3 ]
Kia, A. [2 ]
机构：
[1] Icahn Sch Med Mt Sinai, Pulm Crit Care & Sleep Med, New York, NY 10029 USA
[2] Icahn Sch Med Mt Sinai, Inst Healthcare Delivery Sci, New York, NY 10029 USA
[3] Icahn Sch Med Mt Sinai, Anesthesiol Perioperat & Pain Med, New York, NY 10029 USA
来源：
AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE | 2021年 / 203卷 / 09期
关键词：
D O I：
暂无
中图分类号：
R4 [临床医学];
学科分类号：
1002 ; 100602 ;
摘要：
引用
收藏
页数：2
相关论文
共 50 条
  • [41] Development and validation of an interpretable machine learning model for predicting post-stroke epilepsy
    Yu, Yue
    Chen, Zhibin
    Yang, Yong
    Zhang, Jiajun
    Wang, Yan
    EPILEPSY RESEARCH, 2024, 205
  • [42] Development and validation of ‘Patient Optimizer’ (POP) algorithms for predicting surgical risk with machine learning
    Gideon Kowadlo
    Yoel Mittelberg
    Milad Ghomlaghi
    Daniel K. Stiglitz
    Kartik Kishore
    Ranjan Guha
    Justin Nazareth
    Laurence Weinberg
    BMC Medical Informatics and Decision Making, 24
  • [43] Development and validation of 'Patient Optimizer' (POP) algorithms for predicting surgical risk with machine learning
    Kowadlo, Gideon
    Mittelberg, Yoel
    Ghomlaghi, Milad
    Stiglitz, Daniel K.
    Kishore, Kartik
    Guha, Ranjan
    Nazareth, Justin
    Weinberg, Laurence
    BMC MEDICAL INFORMATICS AND DECISION MAKING, 2024, 24 (01)
  • [44] Development and Validation of an Explainable Machine Learning Model for Predicting Myocardial Injury After Noncardiac Surgery in Two Centers in China: Retrospective Study
    Liu, Chang
    Zhang, Kai
    Yang, Xiaodong
    Meng, Bingbing
    Lou, Jingsheng
    Liu, Yanhong
    Cao, Jiangbei
    Liu, Kexuan
    Mi, Weidong
    Li, Hao
    JMIR AGING, 2024, 7
  • [45] Development and validation of a nomogram for predicting mechanical ventilation need among acutely intoxicated patients with impaired consciousness
    Lashin, Heba Ibrahim
    Sobeeh, Fatma Gaber
    Sobh, Zahraa Khalifa
    HUMAN & EXPERIMENTAL TOXICOLOGY, 2024, 43
  • [46] Predicting success in weaning from mechanical ventilation
    S Vieira
    A Savi
    C Teixeira
    L Nasi
    C Trevisan
    A Guntzel
    R Oliveira
    R Cremonesi
    T Tonietto
    J Hervé
    S Brodt
    F Alves
    J Horer
    N Silva
    Critical Care, 12 (Suppl 2):
  • [47] Predicting success in weaning from mechanical ventilation
    Meade, M
    Guyatt, G
    Cook, D
    Griffith, L
    Sinuff, T
    Kergi, C
    Mancebo, J
    Esteban, A
    Epstein, S
    CHEST, 2001, 120 (06) : 400S - 424S
  • [48] Predicting invasive mechanical ventilation in COVID 19 patients: A validation study
    Statlender, Liran
    Shvartser, Leonid
    Teppler, Shmuel
    Bendavid, Itai
    Kushinir, Shiri
    Azullay, Roy
    Singer, Pierre
    PLOS ONE, 2024, 19 (01):
  • [49] Predicting Hemodynamic Failure Development in PICU Using Machine Learning Techniques
    Comoretto, Rosanna, I
    Azzolina, Danila
    Amigoni, Angela
    Stoppa, Giorgia
    Todino, Federica
    Wolfler, Andrea
    Gregori, Dario
    DIAGNOSTICS, 2021, 11 (07)
  • [50] College students' readiness for connectivist learning: the development and validation of a scale
    Atay, Bulut
    Sumuer, Evren
    INTERNATIONAL JOURNAL OF INFORMATION AND LEARNING TECHNOLOGY, 2021, 38 (02) : 230 - 242
12345