AI model
OtherDoctors in this group are required to use the AI model to assist their diagnoses. The AI pathology model will provide a predicted result for each case.
Not Yet Recruiting
NCT Number: NCT07408167
AI Models in Clinical Pathology Diagnosis: A Multicenter RCT
The investigators plan to conduct a multicenter, prospective, randomized controlled trial to systematically evaluate the incremental value of pathology-based artificial intelligence (AI) models in a pan-disease diagnostic workflow. The study will primarily compare interpretation using an AI-assisted platform with conventional independent slide reading in terms of diagnostic accuracy (e.g., AUC), reading efficiency (e.g., diagnostic time), diagnostic report quality, diagnostic confidence (Likert scale), and pathologists' satisfaction with the AI model. Investigators will also assess superiority among less experienced (junior) pathologists and non-inferiority among more experienced (senior) pathologists. Successful completion of this project will provide high-level prospective evidence to support standardized deployment, quality control, and broader implementation of pathology AI in clinical practice. This trial may also evaluate the potential benefits and risks of using AI tools in medical research.
Not Yet Recruiting
Trial opening soon.
Get NotifiedKey information
Conditions
Age range
18 year–100 year
Sex eligibility
All sexes
Study type
Interventional
Phase
Not applicable
Primary location
The First Hospital Affiliated to AMU SOUTHWEST HOSPITAL, Chongqing, Chongqing Municipality, China
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About this study
In this study, investigators plan to enroll 60 pathologists with varying levels of experience and 2,000 patients requiring pathological diagnosis, with whole-slide images (WSIs) collected.
Who can participate
Healthy volunteers accepted: Yes
Only the study team can determine whether someone qualifies for participation.
Pathologists:
Inclusion criteria
- Voluntarily provide written informed consent.
- Age ≥ 20 years.
- Have completed at least 1 year of training in pathological diagnosis.
Exclusion criteria
- Individuals with reading difficulties or a reading disorder.
- Unwilling to participate in this study.
Patients:
Inclusion criteria
- Voluntarily provide written informed consent.
- Age ≥ 18 years.
- Have available digital pathology images and relevant clinical information.
Exclusion criteria
- Missing data or data quality not meeting the requirements for analysis.
- Deemed unsuitable for participation by the investigator.
- Unwilling to participate in this study.
Treatment and study plan
Control
OtherPathologists will independently diagnose each case based on their own clinical experience, and will record both their time to diagnosis and their diagnostic confidence.
Primary outcomes
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Area under ROC curve (AUC)
Time frame: Assessments will be conducted within one week after the pathologists' diagnoses
Area under the curve
Secondary outcomes
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Diagnostic time per case
Time frame: Measured immediately after the pathologists' diagnosis
Time required for the pathologist to complete the diagnosis of each case in the AI-assisted diagnosis group compared with the independent diagnosis group. Diagnostic time is defined as the duration (in minutes/seconds) from initiating case review to finalizing and submitting the diagnostic report in the study system.
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Pathologists' diagnostic confidence
Time frame: At the time of diagnosis for each case.
Self-reported diagnostic confidence of pathologists for each case in the AI-assisted diagnosis group compared with the independent diagnosis group. Diagnostic confidence will be rated by the reporting pathologist on a [10]-point Likert scale (e.g., 1 = very uncertain to 10 = very confident) immediately after completing the diagnosis. Higher scores indicate greater diagnostic confidence.
Study contacts
Contact information is provided by the study sponsor or research team.
Sponsors and collaborators
Lead sponsor
Nanfang Hospital, Southern Medical University
Other
Registry information
Official study title
Performance of AI Models in the Clinical Pathology Diagnostic Workflow: A Multicenter, Prospective, Randomized Controlled Trial
Important dates
- Study start
- 2026
- Primary completion
- 2028
- Study completion
- 2029
- First posted
- Feb 13, 2026
- Registry last updated
- Feb 13, 2026
OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.
View the official ClinicalTrials.gov record (opens in a new tab)This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.
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