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NCT06553911: AI-MIRID

Exploring the Application Efficacy of Artificial Intelligence (AI) Diagnostic Tools in Medical Imaging (MI) of Respiratory(R) Infectious (I) Disease (D)

Recruiting now NA Last updated 14 August 2024
What this trial tests

NA trial testing Artificial Intelligence-based medical imaging interpretation in Respiratory Infectious Diseases in 2,000 participants. Currently enrolling.

Timeline
1 April 2022
Primary endpoint
1 December 2025
1 December 2026

Quick facts

Lead sponsorHuashan Hospital
PhaseNA
StatusRecruiting now
Study typeINTERVENTIONAL
Allocationrandomized
Designparallel
Maskingnone
Primary purposediagnostic
Enrollment2,000
Start date1 April 2022
Primary completion1 December 2025
Estimated completion1 December 2026
Sites1 location across China

Drugs / interventions tested

Conditions studied

Sponsor

Huashan Hospital

Who can join

Adults 1 to 90, any sex, with Respiratory Infectious Diseases or Artificial Intelligence. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

The early identification and severe warning of acute respiratory infectious diseases are of paramount importance. Utilizing effective means to make correct diagnoses of the source of infection at an early stage is the premise of all effective measures. AI-MID is a research initiative that uses artificial intelligence tools to assist in the clinical medical imaging diagnosis of respiratory diseases, aiming to reduce the time doctors spend reviewing images, increase work efficiency, and enhance the sensitivity and specificity of pneumonia detection, thereby improving the detection rate of pneumonia at the grassroots level. This approach facilitates precise prevention, accurate diagnosis, and precise treatment.

Publications & conference data

No peer-reviewed publications indexed yet for this trial.

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Other Huashan Hospital trials

Trials by the same sponsor.

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Data sources for this page

Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT06553911.

Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing