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Multimodal Deep Learning Model Predicts Pancreatic Cancer Prognosis

NCT06760234 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 247

Last updated 2026-01-07

No results posted yet for this study

Summary

This study describes the development and validation of a deep learning prediction model, which extracts deep learning features from preoperative enhanced CT scans and analyzes postoperative pathological specimens of pancreatic cancer patients. The aim is to predict patient prognosis and response to chemotherapy treatment.

Conditions

  • Pancreatic Adenocarcinoma

Interventions

DIAGNOSTIC_TEST

No Interventions

The high-throughput extraction of quantitative image features from medical images

DIAGNOSTIC_TEST

No Interventions

Immunohistochemical analysis

Sponsors & Collaborators

  • The Fourth Affiliated Hospital of Zhejiang University School of Medicine

    collaborator OTHER

  • Hangzhou Hospital of Traditional Chinese Medicine

    collaborator OTHER

  • Second Affiliated Hospital, School of Medicine, Zhejiang University

    lead OTHER

Principal Investigators

  • Yulian Wu, PhD. · Second Affiliated Hospital of Zhejiang University School of Medicine

Eligibility

Min Age
18 Years
Max Age
90 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-07-05
Primary Completion
2024-12-15
Completion
2026-01-03

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06760234 on ClinicalTrials.gov