Machine learning improves prediction of postoperative outcomes after gastrointestinal surgery : a systematic review and meta-analysis
- Author
- Jane Wang, Francesca Tozzi (UGent) , Amir Ashraf Ganjouei, Fernanda Romero-Hernandez, Jean Feng, Lucia Calthorpe, Maria Castro, Greta Davis, Jacquelyn Withers, Connie Zhou, Zaim Chaudhary, Mohamed Adam, Frederik Berrevoet (UGent) , Adnan Alseidi and Niki Rashidian (UGent)
- Organization
- Project
- Keywords
- Gastroenterology, Surgery, Gastrointestinal surgery, Logistic regression, Machine learning, Meta -analysis, Systematic review, RISK PREDICTION, LOGISTIC-REGRESSION, READMISSION, MODEL, MORTALITY
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01HTM6TNQV6XR42HJ4E2TH0RFN
- MLA
- Wang, Jane, et al. “Machine Learning Improves Prediction of Postoperative Outcomes after Gastrointestinal Surgery : A Systematic Review and Meta-Analysis.” JOURNAL OF GASTROINTESTINAL SURGERY, vol. 28, no. 6, 2024, pp. 956–65, doi:10.1016/j.gassur.2024.03.006.
- APA
- Wang, J., Tozzi, F., Ashraf Ganjouei, A., Romero-Hernandez, F., Feng, J., Calthorpe, L., … Rashidian, N. (2024). Machine learning improves prediction of postoperative outcomes after gastrointestinal surgery : a systematic review and meta-analysis. JOURNAL OF GASTROINTESTINAL SURGERY, 28(6), 956–965. https://doi.org/10.1016/j.gassur.2024.03.006
- Chicago author-date
- Wang, Jane, Francesca Tozzi, Amir Ashraf Ganjouei, Fernanda Romero-Hernandez, Jean Feng, Lucia Calthorpe, Maria Castro, et al. 2024. “Machine Learning Improves Prediction of Postoperative Outcomes after Gastrointestinal Surgery : A Systematic Review and Meta-Analysis.” JOURNAL OF GASTROINTESTINAL SURGERY 28 (6): 956–65. https://doi.org/10.1016/j.gassur.2024.03.006.
- Chicago author-date (all authors)
- Wang, Jane, Francesca Tozzi, Amir Ashraf Ganjouei, Fernanda Romero-Hernandez, Jean Feng, Lucia Calthorpe, Maria Castro, Greta Davis, Jacquelyn Withers, Connie Zhou, Zaim Chaudhary, Mohamed Adam, Frederik Berrevoet, Adnan Alseidi, and Niki Rashidian. 2024. “Machine Learning Improves Prediction of Postoperative Outcomes after Gastrointestinal Surgery : A Systematic Review and Meta-Analysis.” JOURNAL OF GASTROINTESTINAL SURGERY 28 (6): 956–965. doi:10.1016/j.gassur.2024.03.006.
- Vancouver
- 1.Wang J, Tozzi F, Ashraf Ganjouei A, Romero-Hernandez F, Feng J, Calthorpe L, et al. Machine learning improves prediction of postoperative outcomes after gastrointestinal surgery : a systematic review and meta-analysis. JOURNAL OF GASTROINTESTINAL SURGERY. 2024;28(6):956–65.
- IEEE
- [1]J. Wang et al., “Machine learning improves prediction of postoperative outcomes after gastrointestinal surgery : a systematic review and meta-analysis,” JOURNAL OF GASTROINTESTINAL SURGERY, vol. 28, no. 6, pp. 956–965, 2024.
@article{01HTM6TNQV6XR42HJ4E2TH0RFN, author = {{Wang, Jane and Tozzi, Francesca and Ashraf Ganjouei, Amir and Romero-Hernandez, Fernanda and Feng, Jean and Calthorpe, Lucia and Castro, Maria and Davis, Greta and Withers, Jacquelyn and Zhou, Connie and Chaudhary, Zaim and Adam, Mohamed and Berrevoet, Frederik and Alseidi, Adnan and Rashidian, Niki}}, issn = {{1091-255X}}, journal = {{JOURNAL OF GASTROINTESTINAL SURGERY}}, keywords = {{Gastroenterology,Surgery,Gastrointestinal surgery,Logistic regression,Machine learning,Meta -analysis,Systematic review,RISK PREDICTION,LOGISTIC-REGRESSION,READMISSION,MODEL,MORTALITY}}, language = {{eng}}, number = {{6}}, pages = {{956--965}}, title = {{Machine learning improves prediction of postoperative outcomes after gastrointestinal surgery : a systematic review and meta-analysis}}, url = {{http://doi.org/10.1016/j.gassur.2024.03.006}}, volume = {{28}}, year = {{2024}}, }
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