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.

Pathologists:

Inclusion Criteria:

1. Voluntarily provide written informed consent.
2. Age ≥ 20 years.
3. Have completed at least 1 year of training in pathological diagnosis.

Exclusion Criteria:

1. Individuals with reading difficulties or a reading disorder.
2. Unwilling to participate in this study.

Patients:

Inclusion Criteria:

1. Voluntarily provide written informed consent.
2. Age ≥ 18 years.
3. Have available digital pathology images and relevant clinical information.

Exclusion Criteria:

1. Missing data or data quality not meeting the requirements for analysis.
2. Deemed unsuitable for participation by the investigator.
3. Unwilling to participate in this study.