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Validation of an Artificial Intelligence Enabled Diagnostic Support Software (ArtiQ.Spiro) in Primary Care Spirometry Datasets - a Retrospective Analysis

NCT05648227 · Status: ACTIVE_NOT_RECRUITING · Type: OBSERVATIONAL · Enrollment: 1000

Last updated 2025-01-31

No results posted yet for this study

Summary

A retrospective study to evaluate the diagnostic performance of an Artificial Intelligence enabled software (ArtiQ.Spiro) in UK primary care spirometry datasets.

Conditions

  • Respiratory Disease

Sponsors & Collaborators

  • The Hillingdon Hospitals NHS Foundation Trust

    collaborator OTHER_GOV

  • University of Leicester

    collaborator OTHER

  • Southern Health NHS Foundation Trust

    collaborator OTHER

  • Imperial College London

    collaborator OTHER

  • Queen Mary University of London

    collaborator OTHER

  • King's College London

    collaborator OTHER

  • Papworth Hospital NHS Foundation Trust

    collaborator OTHER_GOV

  • King's College Hospital NHS Trust

    collaborator OTHER

  • Royal Brompton & Harefield NHS Foundation Trust

    lead OTHER

Principal Investigators

  • William Man, FRCP · Royal Brompton & Harefield Hospitals

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-07-01
Primary Completion
2025-02-01
Completion
2025-02-28

Countries

  • United Kingdom

Study Locations

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Entities

Companies

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 NCT05648227 on ClinicalTrials.gov