Study on the Construction and Application of a Large Model Corpus for Pancreatic Cancer Based on Real Clinical Cases

July 15, 2026 updated by: Jiang Long, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine
Combining retrospective observational research with artificial intelligence data engineering. Collecting historical electronic medical record data, and through data governance and annotation by artificial medical experts, constructing a structured knowledge base.

Study Overview

Status

Not yet recruiting

Conditions

Study Type

Observational

Enrollment (Estimated)

3000

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

Real pancreatic cancer diagnosis and treatment cases treated in the hospital

Description

Inclusion Criteria:

  1. Real inpatient cases of pancreatic cancer diagnosis and treatment;
  2. Prioritize the inclusion of cases with MDT discussion records, difficult and complex cases, and fatal cases;
  3. Possess complete electronic medical information (including but not limited to: outpatient medical records, inpatient medical records including admission records, progress notes, surgery/procedure records, nursing records, examination and test reports, doctor's orders, discharge/death records, etc.); -

Exclusion Criteria:

  1. Cases that only underwent a brief transition in emergency/outpatient departments and did not form a closed loop of diagnosis and treatment;
  2. Cases with incomplete diagnosis and treatment information and missing key indicators.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Build a high-quality dedicated large model enhanced retrieval knowledge base for pancreatic cancer with a total of no less than 3,000 cases.
Time Frame: May 2028
Combining retrospective observational studies with AI data engineering. Collect historical electronic medical record data and, through data management and expert medical labeling, build a structured knowledge base.
May 2028

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

August 1, 2026

Primary Completion (Estimated)

July 31, 2027

Study Completion (Estimated)

May 31, 2028

Study Registration Dates

First Submitted

July 13, 2026

First Submitted That Met QC Criteria

July 15, 2026

First Posted (Actual)

July 20, 2026

Study Record Updates

Last Update Posted (Actual)

July 20, 2026

Last Update Submitted That Met QC Criteria

July 15, 2026

Last Verified

July 1, 2026

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • IIT2026-152

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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