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Prediction of Expected Length of Hospital Stay Using Machine Learning | Clinical Trials | Clareo Health

WITHDRAWN

Prediction of Expected Length of Hospital Stay Using Machine Learning

NCT04784351•Brigham and Women's Hospital

Summary

This is a retrospective observational study drawing on data from the Brigham and Women's Home Hospital database. Sociodemographic and clinic data from a training cohort were used to train a machine learning algorithm to predict length of stay throughout a patient's admission. This algorithm was then validated in a validation cohort.

Eligibility

Age

18 - No limit years

Sex

ALL

Healthy Volunteers

Inclusion Criteria

•Was a subject in the Brigham and Women's Home Hospital study and has a completed record in the study's database.

Locations (2)

Brigham and Women's Hospital

Boston, Massachusetts, United States

Brigham and Women's Faulkner Hospital

Boston, Massachusetts, United States

Key Dates

Start Date

March 20, 2021

Primary Completion Date

August 1, 2026

Completion Date

December 1, 2026

Last Updated

March 17, 2026

Conditions

InfectionHeart FailureChronic Obstructive Pulmonary DiseaseAsthmaGout FlareChronic Kidney DiseasesHypertensive UrgencyAtrial Fibrillation RapidAnticoagulants; Increased

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RECRUITINGPHASE4

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Data Source & Attribution

This clinical trial information is sourced from ClinicalTrials.gov, a service of the U.S. National Institutes of Health.

ClinicalTrials.gov last update: March 17, 2026Data synced to Clareo: March 29, 2026

Modifications: This data has been reformatted for display purposes. Eligibility criteria have been parsed into inclusion/exclusion sections. Location data has been geocoded to enable distance-based search. For the authoritative and most current information, please visit ClinicalTrials.gov.

Neither the United States Government nor Clareo Health make any warranties regarding the data. Check ClinicalTrials.gov frequently for updates.

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Prediction of Expected Length of Hospital Stay Using Machine Learning

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