A machine learning model for predicting severity-adjusted in-hospital mortality in pneumonia patients

These results suggest that further research is needed on models that adjust for the severity of comorbidities for each diagnosis to more accurately predict health outcomes.

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Publication Details

Journal
Digital Health
Published
2025-05-01
DOI
https://doi.org/10.1177/20552076251351467
Primary Topic
Emergency and Acute Care Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

A machine learning model for predicting severity-adjusted in-hospital mortality in pneumonia patients

Jong-Ho Park, Jihye Lim
Digital Health
Emergency and Acute Care Studies
article

A machine learning model for predicting severity-adjusted in-hospital mortality in pneumonia patients

Jong-Ho Park, Jihye Lim
article en

Abstract

These results suggest that further research is needed on models that adjust for the severity of comorbidities for each diagnosis to more accurately predict health outcomes.

Digital HealthVol. 11
Dong-A University (KR), Daegu University (KR)
Good health and well-being
Openalex Percentile: Top 78%
Emergency and Acute Care Studies
DOIOpen Access PDFOpenAlex
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A machine learning model for predicting severity-adjusted in-hospital mortality in pneumonia patients — Jong-Ho Park, Jihye Lim · Digital Health (2025) | TGRS Research Map | TGRS