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

NCT06553911 · Status: RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 2000

Last updated 2024-08-14

No results posted yet for this study

Summary

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.

Conditions

  • Respiratory Infectious Diseases
  • Artificial Intelligence
  • Medical Imaging

Interventions

OTHER

Artificial Intelligence-based medical imaging interpretation

In the AI interpretation group, using clinical information, imaging data, and corresponding etiological results of the study participants, an AI diagnostic tool is established to specifically recognize patients' chest medical imaging and construct corresponding diagnostic conclusions.

Sponsors & Collaborators

  • Huashan Hospital

    lead OTHER

Study Design

Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
NONE
Model
PARALLEL

Eligibility

Min Age
1 Year
Max Age
90 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2022-04-01
Primary Completion
2025-12-01
Completion
2026-12-01

Countries

  • China

Study Locations

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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 NCT06553911 on ClinicalTrials.gov