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artificial intelligence model and application for early and easy prediction of severity in acute pancreatitis Destination: chapter..1 Children: Item: Title: Abstract Destination: section*.2 Item: Title: 1 | INTRODUCTION Destination: section..1.1 Item: Title: 2 | METHODS Destination: section..1.2 Children: Item: Title: 2.1 | Preliminary settings Destination: subsection..1.2.1 Item: Title: 2.2 | Study design Destination: subsection..1.2.2 Item: Title: 2.3 | Population Destination: subsection..1.2.3 Item: Title: 2.4 | Data collection and management Destination: subsection..1.2.4 Item: Title: 2.5 | Outcome Destination: subsection..1.2.5 Item: Title: 2.6 | Predictors and machine learning Destination: subsection..1.2.6 Item: Title: 2.7 | Explaining the predictions Destination: subsection..1.2.7 Item: Title: 2.8 | Statistical analyses Destination: subsection..1.2.8 Item: Title: 3 | RESULTS Destination: section..1.3 Children: Item: Title: 3.1 | Characteristics of the original cohort Destination: subsection..1.3.1 Item: Title: 3.2 | Machine learning models Destination: subsection..1.3.2 Item: Title: 3.3 | Explaining the predictions Destination: subsection..1.3.3 Item: Title: 3.4 | Validation of the results Destination: subsection..1.3.4 Item: Title: 3.5 | Web application Destination: subsection..1.3.5 Item: Title: 4 | DISCUSSION Destination: section..1.4 Children: Item: Title: 4.1 | Strength and limitations Destination: subsection..1.4.1 Item: Title: 4.2 | Implications for practice Destination: subsection..1.4.2 Item: Title: 5 | CONCLUSION Destination: section..1.5 Item: Title: ACKNOWLEDGEMENTS Destination: section*.4 Item: Title: CONSENT TO PARTICIPATE Destination: section*.6 Item: Title: CONSENT FOR PUBLICATION Destination: section*.8 Item: Title: CONFLICT OF INTEREST Destination: section*.10 Item: Title: ORCID Destination: section*.12 Item: Title: REFERENCES Destination: section*.14 Item: Title: SUPPORTING INFORMATION Destination: section*.16 Info: Title: 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