By integrating retrospective multimodal data such as pathology and imaging, AI technologies offer novel solutions for disease classification, tumor grading, histological and molecular subtyping, selection of chemotherapy regimens, risk stratification, and treatment-response prediction. This research direction not only deepens our understanding of tumor biological characteristics but also provides essential support for precision medicine and individualized therapy. It holds significant theoretical and practical value and has important implications for mitigating strained medical resources and improving the accuracy of therapeutic decision-making, representing a cutting-edge application with substantial translational potential.

Inclusion Criteria:

1. Aged 18-75 years old.
2. Patients with complete pathological slides and clinical information.

Exclusion Criteria:

1.Patients with missing data or specimens not meeting quality control requirements for analysis.

Inclusion criteria comprised patients aged 18-75 years with definitive pathological diagnoses. All cases were retrospectively collected from Nanfang Hospital, Southern Medical University (NFHSMU) .

Requests for the data collected and analyzed in this study will be considered if the application is in line with public benefits and the applicant is willing to sign a data access agreement. Contact can be through the corresponding author.