Author response to: Resection margin status in pancreatic cancer surgery: is it really less important than the N status?

Groen, Jesse V.; Tummers, Willemieke S.; Mieog, J. Sven D.; Swijnenburg, Rutger-Jan

doi:10.1002/bjs.11355

Cited by 1 publication

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“…Logistic regression, random forest, support vector machine, C5.0 decision tree, neural network, bagging algorithm, and AdaBoost algorithm were used to construct the three-year tumour-free survival time (disease-free survival, DFS). e classification and extraction rules of clinical medical data of liver tumours are extracted through the three-year overall survival (OS) model to achieve early prediction and assist clinical diagnosis [4][5][6]. It fulfils early prediction and early treatment, and improves the survival rate of patients with liver tumours.…”

Section: Introductionmentioning

confidence: 99%

Application of the Preoperative Assistant System Based on Machine Learning in Hepatocellular Carcinoma Resection

et al. 2021

Journal of Healthcare Engineering

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To conduct better research in hepatocellular carcinoma resection, this paper used 3D machine learning and logistic regression algorithm to study the preoperative assistance of patients undergoing hepatectomy. In this study, the logistic regression model was analyzed to find the influencing factors for the survival and recurrence of patients. The clinical data of 50 HCC patients who underwent extensive hepatectomy (≥4 segments of the liver) admitted to our hospital from June 2020 to December 2020 were selected to calculate the liver volume, simulated surgical resection volume, residual liver volume, surgical margin, etc. The results showed that the simulated liver volume of 50 patients was 845.2 + 285.5 mL, and the actual liver volume of 50 patients was 826.3 ± 268.1 mL, and there was no significant difference between the two groups (t = 0.425; P > 0.05). Compared with the logistic regression model, the machine learning method has a better prediction effect, but the logistic regression model has better interpretability. The analysis of the relationship between the liver tumour and hepatic vessels in practical problems has specific clinical application value for accurately evaluating the volume of liver resection and surgical margin.

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Section: Introductionmentioning

confidence: 99%

Application of the Preoperative Assistant System Based on Machine Learning in Hepatocellular Carcinoma Resection

et al. 2021

Journal of Healthcare Engineering

View full text Add to dashboard Cite

show abstract

Author response to: Resection margin status in pancreatic cancer surgery: is it really less important than the N status?

Cited by 1 publication

References 6 publications

Application of the Preoperative Assistant System Based on Machine Learning in Hepatocellular Carcinoma Resection

Application of the Preoperative Assistant System Based on Machine Learning in Hepatocellular Carcinoma Resection

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