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The transformation from HCC gene types diagnosis program to machine

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Machine Learning Helps Predict HCC Risk in MASLD

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Measures for response assessment in HCC treatment

Machine learning for individualized prediction of hepatocellular

Machine learningbased clustering differentiates bilateral

Current Status and Analysis of Machine Learning in Hepatocellular Carcinoma

Novel machine learning models outperform risk scores in predicting

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Machine learning models predict hepatocellular carcinoma treatment response

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Machine learning based radiomic models outperform clinical biomarkers

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Frontiers Early Diagnosis of Hepatocellular Carcinoma Using Machine

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Development of a machine learning model to predict early recurrence for

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Machine learning model based on dynamic contrastenhanced ultrasound

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Figure 1 from Comparison between Support Vector Machine and Random

Schematic representation of multistage HCC development from common

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Ultrasonography of Hepatocellular Carcinoma From Diagnosis to Prognosis

Hepatocellular Carcinoma Screening From Current Standard of Care to

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Enhancing ultrasonographic detection of hepatocellular carcinoma with

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The Role of Artificial Intelligence in the Detection and Implementation

Comparison of DeepLearning and Conventional MachineLearning Methods

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Automatic segmentation of hepatocellular carcinoma on dynamic contrast

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Hepatocellular Carcinoma and the Role of Liver Transplantation An

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Hepatic Resection for Hepatocellular Carcinoma Clinics in Liver Disease

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Early warning of hepatocellular carcinoma in cirrhotic patients by

Carcinoma Hepatocelular E Metástases Hepáticas – AVKIU

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MRIBased Deep LearningRadiomicsClinical Nomogram for Predicting Ear

Primary malignant tumours of the liver Clinical Tree

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MachineLearningBased Clinical Biomarker Using CellFree DNA for

Hepatocellular Carcinoma Imaging Advances in 2024 with a Focus on

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