Machine learning model-based prediction of postpancreatectomy acute pancreatitis following pancreaticoduodenectomy: A retrospective cohort study

doi:10.3748/wjg.v31.i8.102071

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World Journal of Gastroenterology

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1007-9327

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

Retrospective Cohort Study

World J Gastroenterol. Feb 28, 2025; 31(8): 102071
Published online Feb 28, 2025. doi: 10.3748/wjg.v31.i8.102071

Table 5 Performance of category boosting model for predicting postpancreatectomy acute pancreatitis based on selected variables

Model	CatBoost
Training AUC	0.837
Testing AUC	0.812
Specificity	0.873
Sensitivity	0.714
MCC	0.535
Kappa	0.529
NPV	0.932
PPV	0.556

CatBoost: Category boosting; AUC: Area under the receiver operating characteristic curve; MCC: Matthews correlation coefficient; NPV: Negative predictive value; PPV: Positive predictive value.

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Citation: Ma JM, Wang PF, Yang LQ, Wang JK, Song JP, Li YM, Wen Y, Tang BJ, Wang XD. Machine learning model-based prediction of postpancreatectomy acute pancreatitis following pancreaticoduodenectomy: A retrospective cohort study. World J Gastroenterol 2025; 31(8): 102071
URL: https://www.wjgnet.com/1007-9327/full/v31/i8/102071.htm
DOI: https://dx.doi.org/10.3748/wjg.v31.i8.102071

Ma JM, Wang PF, Yang LQ, Wang JK, Song JP, Li YM, Wen Y, Tang BJ, Wang XD. Machine learning model-based prediction of postpancreatectomy acute pancreatitis following pancreaticoduodenectomy: A retrospective cohort study. World J Gastroenterol 2025; 31(8): 102071 [PMID: 40062328 DOI: 10.3748/wjg.v31.i8.102071]

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