Mortality prediction of inpatients with NSTEMI in a premier hospital in China based on stacking model

The Stacking model proposed in this paper can integrate the advantages of LR, DT, SVM, RF, ADB, ET and GBDT models to achieve better prediction performance. This model can provide valuable insights for physicians to identify high-risk patients more precisely and timely, thereby maximizing the potential for early clinical interventions to reduce the mortality rate.

Authors

Yu Zhang (ORCID: https://orcid.org/0000-0003-2558-0606)
Li Wang (ORCID: https://orcid.org/0000-0001-6673-3141)
Feng Li (ORCID: https://orcid.org/0000-0001-9274-1137)
Caiyun Li (ORCID: https://orcid.org/0000-0002-6863-2173)
Hongzeng Xu (ORCID: https://orcid.org/0009-0004-7541-4643)

Institutions

Liaoning Provincial People's Hospital (CN)
Dalian Maritime University (CN)
Zhejiang Gongshang University (CN)
China Medical University (CN)

Publication Details

Journal: PLoS ONE
Published: 2024-12-31
DOI: https://doi.org/10.1371/journal.pone.0312448
Citations: 3
Primary Topic: Machine Learning in Healthcare
Type: article
Field-Weighted Citation Impact: 1.04

Funders

Natural Science Foundation of Liaoning Province

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article

Mortality prediction of inpatients with NSTEMI in a premier hospital in China based on stacking model

Yu Zhang, Li Wang, Feng Li, Caiyun Li et al.

Dec 31, 2024

3 citations

PLoS ONE

Machine Learning in Healthcare

1.04

article

Mortality prediction of inpatients with NSTEMI in a premier hospital in China based on stacking model

Yu Zhang, Li Wang, Feng Li, Caiyun Li, Hongzeng Xu

December 31, 2024article en

3 citations

Abstract

The Stacking model proposed in this paper can integrate the advantages of LR, DT, SVM, RF, ADB, ET and GBDT models to achieve better prediction performance. This model can provide valuable insights for physicians to identify high-risk patients more precisely and timely, thereby maximizing the potential for early clinical interventions to reduce the mortality rate.

PLoS ONEVol. 19(12)

Liaoning Provincial People's Hospital (CN), Dalian Maritime University (CN), Zhejiang Gongshang University (CN), China Medical University (CN)

Natural Science Foundation of Liaoning Province

Good health and well-being

Openalex Percentile: Top 18%

Machine Learning in Healthcare

1.04

DOI Open Access PDF OpenAlex

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Mortality prediction of inpatients with NSTEMI in a premier hospital in China based on stacking model — Yu Zhang, Li Wang, et al. · PLoS ONE (2024) | TGRS Research Map | TGRS