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Prediction of Expected Length of Hospital Stay Using Machine Learning

NCT04784351 · Status: WITHDRAWN · Type: OBSERVATIONAL

Last updated 2026-03-17

No results posted yet for this study

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.

Conditions

Sponsors & Collaborators

  • Biofourmis Inc.

    collaborator INDUSTRY

  • Brigham and Women's Hospital

    lead OTHER

Principal Investigators

  • David Levine, MD MPH MA · Associate Physician

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2021-03-20
Primary Completion
2026-08-01
Completion
2026-12-01

Countries

  • United States

Study Locations

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04784351 on ClinicalTrials.gov