This project proposes to collect prospective multimodal data-such as pathology, imaging, and clinical information-and to perform integrative analyses. AI technologies can offer novel solutions for disease classification, tumor grading, histological subtyping, molecular subtyping, selection of chemotherapy regimens, risk stratification, treatment response prediction, report generation, and intelligent question-answering. This research provides important support for precision medicine and individualized treatment and has significant theoretical and practical implications. Conducting a prospective randomized controlled study better aligns with clinical application requirements and can accelerate the comprehensive deployment of AI systems.
Study Type
OBSERVATIONAL
Enrollment
2,000
Nanfang Hospital, Southern Medical University
Guangzhou, Guangdong, China
Zhongshan City People's Hospital
Zhongshan, Guangdong, China
Area under ROC curve (AUC)
Area under the curve
Time frame: Diagnostic evaluation will be performed within 1 week when the WSIs or CT are obtained
Specificity
The true negative rate (TNR) of the diagnostic platform, which is the ratio between the number of negative individuals correctly categorized by platform and the total number of actual negative individuals (%).
Time frame: Diagnostic evaluation will be performed within 1 week when the WSIs or CT are obtained
Sensitivity
The true positive rate (TPR) of the diagnostic platform, which is the ratio between the number of positive individuals correctly categorized by platform and the total number of actual positive individuals (%).
Time frame: Diagnostic evaluation will be performed within 1 week when the WSIs or CT are obtained
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