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Study on big data algorithms for pancreatic disease diagnosis and treatment driven by artificial intelligence

Study on big data algorithms for pancreatic disease diagnosis and treatment driven by artificial intelligence

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600121006
Enrollment
Unknown
Registered
2026-03-24
Start date
2026-04-01
Completion date
Unknown
Last updated
2026-03-30

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

pancreatic cancer

Interventions

retrospective cohort (Diagnosed with pancreatic cancer or benign pancreatic disease):None
A prospective cohort study of a high-risk population:None

Sponsors

Peking Union Medical College Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: The inclusion criteria for the retrospective cohort were as follows: 1. Patients with any of the following diagnoses: (1) Pancreatic cancer (2) Pancreatic cystic tumors(3) Solid pseudopapillary tumor of the pancreas (SPT) (4) Pancreatic neuroendocrine tumor (NET) (5) Patients with pancreatitis or those with a history of pancreatitis (6) Malignant tumors of non-pancreatic origin (7) Benign disease control groups (8) Healthy individuals 2. Age at diagnosis: >=18 years old. The inclusion criteria for the prospective cohort are: 1. There is at least one high-risk factor, including (1) a history of pancreatitis (2) pancreatic cystic tumors (3) Newly diagnosed diabetic patients (4) persistently or progressively elevated tumor markers (5) lost weight for unknown reasons (6) People with a family history of pancreatic cancer (7)hereditary syndromes related to pancreatic cancer (8) Other high-risk factors for pancreatic cancer. 2. Age at enrollment: >=18 years old.

Exclusion criteria

Exclusion criteria: Individuals who cannot provide informed consent.

Design outcomes

Primary

MeasureTime frame
Area under curve, AUC;Sensitivity;Specificity;Positive predictive value;Negative Predictive Value;

Countries

China

Contacts

Public ContactWenming Wu

Peking Union Medical College Hospital

wuwm@pumch.cn+86 10 69156038

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Apr 4, 2026