Application of machine learning models on predicting the length of hospital stay in fragility fracture patients.

Journal Information

Full Title: BMC Med Inform Decis Mak

Abbreviation: BMC Med Inform Decis Mak

Country: Unknown

Publisher: Unknown

Language: N/A

Publication Details

Subject Category: Medical Informatics

Available in Europe PMC: Yes

Available in PMC: Yes

PDF Available: No

Transparency Score
3/6
50.0% Transparent
Transparency Indicators
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Core Indicators
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Evidence found in paper:

"Declarations Ethics approval and consent to participateEthical approval was obtained from the ethics review board of the Joint Chinese University of Hong Kong – New Territories East Cluster Clinical Research Ethics Committee (Ref. No.: CRE2022.004). The study protocol complied with the Declaration of Helsinki.Informed consent has been obtained from all participants. Consent for publicationNot applicable. Competing interestsThe authors declare no competing interests. Competing interests The authors declare no competing interests."

Evidence found in paper:

"Funding No Funding. All authors did not receive any funding from the manufacturer for this study."

Protocol Registration
Open Access
Paper is freely available to read
Additional Indicators
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Novelty Statement
Assessment Info

Tool: rtransparent

OST Version: N/A

Last Updated: Aug 05, 2025