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.
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.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
OTHER
Masking
SINGLE
Enrollment
2,060
Doctors 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.
Pathologists will independently diagnose each case based on their own clinical experience, and will record both their time to diagnosis and their diagnostic confidence.
The First Hospital Affiliated to AMU SOUTHWEST HOSPITAL
Chongqing, Chongqing Municipality, China
Nanfang Hospital, Southern Medical University
Guangzhou, Guangdong, China
The First Affiliated Hospital of Zhengzhou University
Zhengzhou, Henan, China
Area under ROC curve (AUC)
Area under the curve
Time frame: Assessments will be conducted within one week after the pathologists' diagnoses
Diagnostic time per case
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.
Time frame: Measured immediately after the pathologists' diagnosis
Pathologists' diagnostic confidence
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.
Time frame: At the time of diagnosis for each case.
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