Development and external evaluation of an interpretable machine-learning model for early prediction of organ failure in higher-risk acute pancreatitis patients: A multicentre cohort study.

Wu D, Cai W, Chen C, Chen M, Lv Y, Huang Y, Evans A, Lin J, Latawiec D, Kattakayam A, Mukherjee R, Huang W, Xia Q, Xiao J, Su C, Peng J, Jiang K, Sutton R

Open source

DOI
10.1371/journal.pdig.0001735
Published
2026 Sep
Container
PLOS digital health
Publisher
Not recorded
Open access
yes

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BibTeX

@article{allodium:10.1371/journal.pdig.0001735,
  title = {Development and external evaluation of an interpretable machine-learning model for early prediction of organ failure in higher-risk acute pancreatitis patients: A multicentre cohort study.},
  author = {Wu D and Cai W and Chen C and Chen M and Lv Y and Huang Y and Evans A and Lin J and Latawiec D and Kattakayam A and Mukherjee R and Huang W and Xia Q and Xiao J and Su C and Peng J and Jiang K and Sutton R},
  year = {2026},
  journal = {PLOS digital health},
  doi = {10.1371/journal.pdig.0001735},
  url = {https://doi.org/10.1371/journal.pdig.0001735}
}

RIS

TY  - JOUR
TI  - Development and external evaluation of an interpretable machine-learning model for early prediction of organ failure in higher-risk acute pancreatitis patients: A multicentre cohort study.
AU  - Wu D
AU  - Cai W
AU  - Chen C
AU  - Chen M
AU  - Lv Y
AU  - Huang Y
AU  - Evans A
AU  - Lin J
AU  - Latawiec D
AU  - Kattakayam A
AU  - Mukherjee R
AU  - Huang W
AU  - Xia Q
AU  - Xiao J
AU  - Su C
AU  - Peng J
AU  - Jiang K
AU  - Sutton R
PY  - 2026
JO  - PLOS digital health
DO  - 10.1371/journal.pdig.0001735
UR  - https://doi.org/10.1371/journal.pdig.0001735
ER  - 

APA

D, W., W, C., C, C., M, C., Y, L., Y, H., A, E., J, L., D, L., A, K., R, M., W, H., Q, X., J, X., C, S., J, P., K, J., & R, S. (2026). Development and external evaluation of an interpretable machine-learning model for early prediction of organ failure in higher-risk acute pancreatitis patients: A multicentre cohort study.. PLOS digital health. https://doi.org/10.1371/journal.pdig.0001735

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