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The research objective of this project is to conduct a large-scale and prospective real-world validation of the Pancreatic Cancer Screening Model PANDA, which was developed based on deep learning and plain CT scans in previous studies. This validation will be carried out across different scenarios at the First Affiliated Hospital of Zhejiang University, leveraging clinical big data. The goal is to verify the model's role in suggesting and supplementing the diagnosis of PDAC in clinical practice, thereby laying the groundwork for large-scale opportunistic screening of PDAC.
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This study focuses on potential cases of clinically missed PDAC. It aims to evaluate the pancreatic cancer screening model PANDA, based on deep learning and non-enhanced CT scans, in a prospective real-world cohort from multiple clinical scenarios at the First Affiliated Hospital of Zhejiang University. The study will track patients with negative imaging reports but positive PANDA model findings, verifying their pathology through gold standard examinations to assess PANDA's efficacy. It aims to validate the model's utility, applicability, sensitivity, and specificity.
Based on these objectives, the study will undertake the following:
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200,000 participants in 3 patient groups
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Qi Zhang, Associate professor
Data sourced from clinicaltrials.gov
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