Health Condition 1: K859- Acute pancreatitis, unspecified
Conditions
Interventions
Intervention1: Nil: Nil
Sponsors
Saveetha Institute Of Medical And Technical Sciences
Eligibility
Inclusion criteria
Inclusion criteria: Patients diagnosed with acute pancreatitis based on clinical biochemical and imaging criteria Patients who underwent 128 slice non contrast ct abdomen Patients with adequate image quality for analysis Patients willing to provide consent for participation
Exclusion criteria
Exclusion criteria: Patients below 18 years of age Patients with chronic pancreatitis without acute exacerbation Patients with prior pancreatic or biliary surgery Patients with pancreatic malignancy Patients with inadequate or poor quality ct images Pregnant patients
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Diagnostic accuracy of ai model for detection of peripancreatic fluid collections on non contrast CT including sensitivity specificity positive predictive value negative predictive value and AUC ROCTimepoint: At time of CT imaging and analysis | — |
Secondary
| Measure | Time frame |
|---|---|
| Dice similarity coefficient for AI based segmentation of fluid collectionsTimepoint: At time of image analysis | — |
Countries
India
Contacts
Public ContactAmogh Diwakar
Saveetha Institute of Medical and Technical Sciences
Outcome results
None listed