Predicting High‐Flow Nasal Cannula Oxygen Therapy Failure in Patients With Acute Hypoxaemic Respiratory Failure Using Machine Learning: Model Development and External Validation

Authors

Xiaoyu Zheng (ORCID: https://orcid.org/0000-0003-4286-9196)
Jun Lyu (ORCID: https://orcid.org/0000-0002-2237-8771)
Mei Feng (ORCID: https://orcid.org/0000-0002-8928-8228)
Hongtao Cheng (ORCID: https://orcid.org/0000-0002-9025-8923)
Zichen Wang (ORCID: https://orcid.org/0000-0002-9369-6611)
Yonglan Tang
Xiaoshen Zhang (ORCID: https://orcid.org/0000-0002-9984-8380)

Institutions

Jinan University (CN)
First Affiliated Hospital of Jinan University (CN)

Publication Details

Journal: Journal of Clinical Nursing
Published: 2024-10-28
DOI: https://doi.org/10.1111/jocn.17518
Citations: 5
Primary Topic: Respiratory Support and Mechanisms
Type: article
Field-Weighted Citation Impact: 2.09

Funders

Jinan University

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article

Predicting High‐Flow Nasal Cannula Oxygen Therapy Failure in Patients With Acute Hypoxaemic Respiratory Failure Using Machine Learning: Model Development and External Validation

Xiaoyu Zheng, Jun Lyu, Mei Feng, Hongtao Cheng et al.

Oct 28, 2024

5 citations

Journal of Clinical Nursing

Respiratory Support and Mechanisms

2.09

article

Predicting High‐Flow Nasal Cannula Oxygen Therapy Failure in Patients With Acute Hypoxaemic Respiratory Failure Using Machine Learning: Model Development and External Validation

Xiaoyu Zheng, Jun Lyu, Mei Feng, Hongtao Cheng, Zichen Wang, Yonglan Tang, Xiaoshen Zhang

October 28, 2024article en

5 citations

Abstract

No abstract available for this paper.

Journal of Clinical NursingVol. 34(9)

Jinan University (CN), First Affiliated Hospital of Jinan University (CN)

Jinan University

Good health and well-being

Openalex Percentile: Top 12%

Respiratory Support and Mechanisms

2.09

DOI Open Access PDF OpenAlex

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