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

Abstract

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.

Different applications of Artificial Intelligence in liver cancer: a scoping review – part II, from treatment planning and efficacy assessment to prognosis prediction and follow-up. (Preprint)

“…However, when multiple interventions are combined in a large period, it is hard to foresee which patient will benefit from a specific strategy and which one will not respond and should be addressed to systemic therapy or best supportive care avoiding unbeneficial invasive procedures. For 6 Thailand SPECT/CT-scan 56 CNN, automatic Segmentation for liver TARE planning (HCC) Wei, 2021 8 Germany/China US/CT-scan 52 CNN, automatic Probe plane identification for liver TA planning (HCC) De Landro, 2021 9 Italy HSI -CNN, automatic Prediction of ablation margins for LA planning (HCC) Lv, 2021 10 China CT-scan 50 ML Liver remnant volume and resection plane prediction (HCC) Takamoto, 2022 12 Japan CT-scan 144 CNN, automatic Liver and tumor segmentation and volume calculation (HCC, ICC, Met, benign lesions) Zhu, 2023 14 China MR/CT-scan radiomics, IGC 190 ML Liver functional reserve evaluation (HCC) Mo, 2022 15 USA clinical, biochemical 237 ML Treatment planning (SBRT vs. TA) after TACE (HCC) Boldanova, 2021 17 Switzerland clinical, radiological, transcriptomics 33 ML Prediction of TACE outcome (HCC) Sun, 2020 18 China MR radiomics 84 ML Prediction of TACE outcome (HCC) Hsu, 2022 19 Taiwan biochemical 82 ML Prediction of Lenvatinib response (HCC) Luo, 2022 20 China genomics/transcriptomics 450 ANN, ML Prediction of chemotherapy response (HCC)…”

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

“…This article has been retracted by Hindawi following an investigation undertaken by the publisher [ 1 ]. This investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process: Discrepancies in scope Discrepancies in the description of the research reported Discrepancies between the availability of data and the research described Inappropriate citations Incoherent, meaningless and/or irrelevant content included in the article Peer-review manipulation …”

“…Tis article has been retracted by Hindawi following an investigation undertaken by the publisher [1]. Tis investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process:…”