Prediction and evaluation of the severity of acute respiratory distress syndrome following severe acute pancreatitis using an artificial neural network algorithm model.

Journal: HPB : the official journal of the International Hepato Pancreato Biliary Association

PMID: 30591306

Abstract

BACKGROUND: To predict the risk and severity of acute respiratory distress syndrome (ARDS) following severe acute pancreatitis (SAP) by artificial neural networks (ANNs) model.

Authors

Yang Fei

Surgical Intensive Care Unit (SICU), Department of General Surgery, Jinling Hospital, Medical School of Nanjing University, No. 305 Zhongshan East Road, Nanjing 210002, China.
Kun Gao

a State Key Laboratory of Applied Organic Chemistry, College of Chemistry and Chemical Engineering , Lanzhou University , Lanzhou , People's Republic of China.
Wei-Qin Li

Surgical Intensive Care Unit (SICU), Department of General Surgery, Jinling Hospital, Medical School of Nanjing University, No. 305 Zhongshan East Road, Nanjing 210002, China. Electronic address: chamskuler@163.com.

Keywords

Adult Decision Support Techniques Female Humans Male Middle Aged Neural Networks, Computer Pancreatitis Predictive Value of Tests Prognosis Reproducibility of Results Respiratory Distress Syndrome Risk Assessment Risk Factors Severity of Illness Index

External Resources

View on PubMed Access via DOI PubMed (30591306)

Prediction and evaluation of the severity of acute respiratory distress syndrome following severe acute pancreatitis using an artificial neural network algorithm model.

Abstract

Authors

Keywords

External Resources

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