An Artificial Intelligence Model for Aiding Claudin18.2 Expression Diagnosis in Gastric Adenocarcinoma

Condition(s) studied

Study summary

The investigators plan to develop a deep learning-based automatic interpretation model for Claudin18.2(CLDN18.2) using the institution's and multiple other centers' extensive pathological resources of digestive system adenocarcinomas. This study will not only strictly follow the latest domestic expert consensus and standards, but also aims to address current pain points in manual interpretation. It seeks to provide technical support for standardizing, objectifying, and streamlining CLDN18.2 testing, thereby advancing the application of precision medicine in the diagnosis and treatment of digestive system diseases. The project has clear clinical necessity and broad application prospects.

Eligibility

Primary outcome measure(s)

• Area under ROC curve (AUC) — Diagnostic evaluation will be performed within 1 week when the whole slide images(WSIs) are obtained.
  Area under the curve

Trial sites (2)

More Nanfang Hospital, Southern Medical University trials in China