Exploring the Application Efficacy of Artificial Intelligence (AI) Diagnostic Tools in Medical Imaging (MI) of Respiratory(R) Infectious (I) Disease (D)
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: Artificial Intelligence-based medical imaging interpretation.
- Who it may be relevant to
- Registry conditions: Respiratory Infectious Diseases, Artificial Intelligence, Medical Imaging. Basic parameters: 1 year — 90 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- China
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Overview
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.
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.
Primary outcome measures
- Evaluating the Diagnostic Efficacy of Artificial Intelligence Diagnostic Tools in Medical Imaging of Respiratory Infectious Diseases [Time frame: 2 years]
Secondary outcome measures (1)
- Utilizing artificial intelligence tools for early identification and severe warning of respiratory infectious diseases [Time frame: 2 years]
Eligibility criteria
Inclusion criteria
- 1-90 years old, gender not specified.
- Exhibits symptoms of respiratory tract infection
- Must have etiological examination results
- Must have imaging data;
Exclusion criteria
- Severe artifacts in medical images
- Clinical diagnosis indicates concurrent pulmonary edema
- Dual review results in unclear diagnosis or potential misdiagnosis
- Other situations that may cause difficulties in reading the films, or as determined by the researcher, the study participant is deemed unsuitable for enrollment.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: Yes
Study design
- Allocation
- Randomized
- Model
- Parallel assignment
- Masking
- Open label
- Primary purpose
- Diagnostic
Study locations
China · 1 center
- Huashan Hospital — Shanghai
Identifiers
NCT: NCT06553911 · AI-MIRID