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Machine Learning-Based 30-Day Hospital Readmission Predictions for COPD Patients Using Physical Acti...

Machine Learning-Based 30-Day Hospital Readmission Predictions for COPD Patients Using Physical Acti...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_6f9b17735c9f4644a888a0d2c69d8db8

Machine Learning-Based 30-Day Hospital Readmission Predictions for COPD Patients Using Physical Activity Data of Daily Living with Accelerometer-Based Device

About this item

Full title

Machine Learning-Based 30-Day Hospital Readmission Predictions for COPD Patients Using Physical Activity Data of Daily Living with Accelerometer-Based Device

Publisher

Basel: MDPI AG

Journal title

Biosensors (Basel), 2022-08, Vol.12 (8), p.605

Language

English

Formats

Publication information

Publisher

Basel: MDPI AG

More information

Scope and Contents

Contents

Chronic obstructive pulmonary disease (COPD) is a significantly concerning disease, and is ranked highest in terms of 30-day hospital readmission. Generally, physical activity (PA) of daily living reflects the health status and is proposed as a strong indicator of 30-day hospital readmission for patients with COPD. This study attempted to predict 3...

Alternative Titles

Full title

Machine Learning-Based 30-Day Hospital Readmission Predictions for COPD Patients Using Physical Activity Data of Daily Living with Accelerometer-Based Device

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_6f9b17735c9f4644a888a0d2c69d8db8

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_6f9b17735c9f4644a888a0d2c69d8db8

Other Identifiers

ISSN

2079-6374

E-ISSN

2079-6374

DOI

10.3390/bios12080605

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