The application of machine learning for identifying frailty in older patients during hospital admission

Our results demonstrated that some easily accessed parameters from the hospital clinical data system can be used to predict frailty in older hospitalized patients using supervised ML methods.

Authors

Institutions

Publication Details

Journal
BMC Medical Informatics and Decision Making
Published
2024-09-27
DOI
https://doi.org/10.1186/s12911-024-02684-z
Citations
5
Primary Topic
Frailty in Older Adults
Type
article
Field-Weighted Citation Impact
1.72

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The application of machine learning for identifying frailty in older patients during hospital admission

Shih-Ming Huang, Cheng-Fu Lin, Min-Shian Wang, Chieh‐Liang Wu et al.
5 citations
BMC Medical Informatics and Decision Making
Frailty in Older Adults
1.72
article

The application of machine learning for identifying frailty in older patients during hospital admission

Shih-Ming Huang, Cheng-Fu Lin, Min-Shian Wang, Chieh‐Liang Wu, Shih-Yi Lin, Yin-Yi Chou, Pei-Hua Lee, Yu-Shan Lee
article en
5 citations

Abstract

Our results demonstrated that some easily accessed parameters from the hospital clinical data system can be used to predict frailty in older hospitalized patients using supervised ML methods.

BMC Medical Informatics and Decision MakingVol. 24(1)
National Chung Hsing University (TW), Taichung Veterans General Hospital (TW)
Taichung Veterans General Hospital
Gender equality
Openalex Percentile: Top 16%
Frailty in Older Adults
1.72
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.