Predictive analytics with ensemble modeling in laparoscopic surgery: A technical note
Article Properties
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LanguageEnglish
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DOI (url)
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Publication Date2022/03/01
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Indian UGC (journal)
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Refrences15
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Citations55
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Zhongheng Zhang ORCID (unauthenticated)
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Lin Chen ORCID (unauthenticated)
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Ping Xu
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Yucai Hong
Cite
Zhang, Zhongheng, et al. “Predictive Analytics With Ensemble Modeling in Laparoscopic Surgery: A Technical Note”. Laparoscopic, Endoscopic and Robotic Surgery, vol. 5, no. 1, 2022, pp. 25-34, https://doi.org/10.1016/j.lers.2021.12.003.
Zhang, Z., Chen, L., Xu, P., & Hong, Y. (2022). Predictive analytics with ensemble modeling in laparoscopic surgery: A technical note. Laparoscopic, Endoscopic and Robotic Surgery, 5(1), 25-34. https://doi.org/10.1016/j.lers.2021.12.003
Zhang, Zhongheng, Lin Chen, Ping Xu, and Yucai Hong. “Predictive Analytics With Ensemble Modeling in Laparoscopic Surgery: A Technical Note”. Laparoscopic, Endoscopic and Robotic Surgery 5, no. 1 (2022): 25-34. https://doi.org/10.1016/j.lers.2021.12.003.
Zhang Z, Chen L, Xu P, Hong Y. Predictive analytics with ensemble modeling in laparoscopic surgery: A technical note. Laparoscopic, Endoscopic and Robotic Surgery. 2022;5(1):25-34.
Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| A guide to machine learning for biologists | Nature Reviews Molecular Cell Biology |
| 549 | 2022 |
Dynamic prediction for clinically relevant pancreatic fistula: a novel prediction model for laparoscopic pancreaticoduodenectomy | BMC Surgery |
| 7 | 2021 |
Bagging Machine Learning Algorithms: A Generic Computing Framework Based on Machine-Learning Methods for Regional Rainfall Forecasting in Upstate New York | Informatics |
| 7 | 2021 |
| Risk of complication at the time of laparoscopic hysterectomy: a prediction model built from the National Surgical Quality Improvement Program database | American Journal of Obstetrics and Gynecology |
| 13 | 2020 |
| A gentle introduction to artificial neural networks | Annals of Translational Medicine |
| 46 | 2016 |
Citations
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| Thank you to our wonderful peer reviewers and authors | Laparoscopic, Endoscopic and Robotic Surgery | 2024 | ||
| Construction and validation of a risk-prediction model for anastomotic leakage after radical gastrectomy: A cohort study in China | Laparoscopic, Endoscopic and Robotic Surgery | 2024 | ||
Interpretable prediction models for disability in older adults with hypertension: the Chinese Longitudinal Healthy Longevity and Happy Family Study | Psychogeriatrics |
| 2024 | |
Identifying metabolic dysfunction-associated steatotic liver disease in patients with hypertension and pre-hypertension: An interpretable machine learning approach | DIGITAL HEALTH |
| 2024 | |
Data analytics approach for short- and long-term mortality prediction following acute non-ST-elevation myocardial infarction (NSTEMI) and Unstable Angina (UA) in Asians | PLOS ONE |
| 2024 |
Citations Analysis
The category
Medicine: Medicine (General) 31
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Editorial: Clinical application of artificial intelligence in emergency and critical care medicine, volume III and was published in 2022. The most recent citation comes from a 2024 study titled Development and performance assessment of novel machine learning models for predicting postoperative pneumonia in aneurysmal subarachnoid hemorrhage patients: external validation in MIMIC-IV. This article reached its peak citation in 2022, with 37 citations. It has been cited in 32 different journals, 65% of which are open access. Among related journals, the Frontiers in Medicine cited this research the most, with 9 citations. The chart below illustrates the annual citation trends for this article.