Interpretable mortality prediction model for ICU patients with pneumonia: using shapley additive explanation method

Interpretable predictive models enhance mortality risk assessment for pneumonia patients in the ICU, fostering transparency. AST emerged as the foremost predictor, followed by patient age, albumin, BMI et al. These insights, rooted in strong correlations with mortality, facilitate improved clinical decision-making and resource allocation.

Authors

Jiaxi Li (ORCID: https://orcid.org/0000-0002-9820-8461)
Yan Tang (ORCID: https://orcid.org/0000-0002-5513-6453)
Shengyang He (ORCID: https://orcid.org/0000-0003-1301-3524)
Yu Zhang (ORCID: https://orcid.org/0009-0008-9991-3331)

Institutions

Sichuan University (CN)
West China Hospital of Sichuan University (CN)
Maternal and Child Health Hospital of Sichuan Province (CN)

Publication Details

Journal: BMC Pulmonary Medicine
Published: 2024-09-13
DOI: https://doi.org/10.1186/s12890-024-03252-x
Citations: 10
Primary Topic: Machine Learning in Healthcare
Type: article
Field-Weighted Citation Impact: 3.47

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article

Interpretable mortality prediction model for ICU patients with pneumonia: using shapley additive explanation method

Jiaxi Li, Yan Tang, Shengyang He, Yu Zhang

Sep 13, 2024

10 citations

BMC Pulmonary Medicine

Machine Learning in Healthcare

3.47

article

Interpretable mortality prediction model for ICU patients with pneumonia: using shapley additive explanation method

Jiaxi Li, Yan Tang, Shengyang He, Yu Zhang

September 13, 2024article en

10 citations

Abstract

Interpretable predictive models enhance mortality risk assessment for pneumonia patients in the ICU, fostering transparency. AST emerged as the foremost predictor, followed by patient age, albumin, BMI et al. These insights, rooted in strong correlations with mortality, facilitate improved clinical decision-making and resource allocation.

BMC Pulmonary MedicineVol. 24(1)

Sichuan University (CN), West China Hospital of Sichuan University (CN), Maternal and Child Health Hospital of Sichuan Province (CN)

Good health and well-being

Openalex Percentile: Top 7%

Machine Learning in Healthcare

3.47

DOI Open Access PDF OpenAlex

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Interpretable mortality prediction model for ICU patients with pneumonia: using shapley additive explanation method — Jiaxi Li, Yan Tang, et al. · BMC Pulmonary Medicine (2024) | TGRS Research Map | TGRS