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Carcinoma, Hepatocellular

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Prediction of Microvascular Invasion of Hepatocellular Carcinoma Based on Preoperative Diffusion-Weighted MR Using Deep Learning.

Academic radiology
RATIONALE AND OBJECTIVES: To investigate the value of diffusion-weighted magnetic resonance imaging for the prediction of microvascular invasion (MVI) of Hepatocellular Carcinoma (HCC) using Convolutional Neural Networks (CNN).

Exploring prognostic indicators in the pathological images of hepatocellular carcinoma based on deep learning.

Gut
OBJECTIVE: Tumour pathology contains rich information, including tissue structure and cell morphology, that reflects disease progression and patient survival. However, phenotypic information is subtle and complex, making the discovery of prognostic i...

Prediction of early recurrence of hepatocellular carcinoma after resection using digital pathology images assessed by machine learning.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Hepatocellular carcinoma (HCC) is a representative primary liver cancer caused by long-term and repetitive liver injury. Surgical resection is generally selected as the radical cure treatment. Because the early recurrence of HCC after resection is as...

Development of machine learning-based clinical decision support system for hepatocellular carcinoma.

Scientific reports
There is a significant discrepancy between the actual choice for initial treatment option for hepatocellular carcinoma (HCC) and recommendations from the currently used BCLC staging system. We develop a machine learning-based clinical decision suppor...

Multi-Responsive Bottlebrush-Like Unimolecules Self-Assembled Nano-Riceball for Synergistic Sono-Chemotherapy.

Small methods
Improved drug loading content, bioavailability, and controlled release in targeted tissue have been major bottlenecks in the design of precision nanomedicine. Herein, a tumor-specific and multiple-stimuli responsive nano-riceball is proposed and vali...

Preoperative identification of microvascular invasion in hepatocellular carcinoma by XGBoost and deep learning.

Journal of cancer research and clinical oncology
PURPOSE: Microvascular invasion (MVI) is a valuable predictor of survival in hepatocellular carcinoma (HCC) patients. This study developed predictive models using eXtreme Gradient Boosting (XGBoost) and deep learning based on CT images to predict MVI...

Artificial neural network model for preoperative prediction of severe liver failure after hemihepatectomy in patients with hepatocellular carcinoma.

Surgery
BACKGROUND: Posthepatectomy liver failure is a worrisome complication after major hepatectomy for hepatocellular carcinoma and is the leading cause of postoperative mortality. Recommendations for hepatectomy for hepatocellular carcinoma are based on ...

Robot-assisted ultrasound navigation platform for 3D HIFU treatment planning: Initial evaluation for conformal interstitial ablation.

Computers in biology and medicine
Interstitial Ultrasound-guided High Intensity Focused Ultrasound (USgHIFU) therapy has the potential to deliver ablative treatments which conform to the target tumor. In this study, a robot-assisted US-navigation platform has been developed for 3D US...