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Carcinoma, Hepatocellular

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Deep learning enables the discovery of a novel cuproptosis-inducing molecule for the inhibition of hepatocellular carcinoma.

Acta pharmacologica Sinica
Hepatocellular carcinoma (HCC) is one of the most common and deadly cancers in the world. The therapeutic outlook for HCC patients has significantly improved with the advent and development of systematic and targeted therapies such as sorafenib and l...

A multitask deep learning radiomics model for predicting the macrotrabecular-massive subtype and prognosis of hepatocellular carcinoma after hepatic arterial infusion chemotherapy.

La Radiologia medica
BACKGROUND: The macrotrabecular-massive (MTM) is a special subtype of hepatocellular carcinoma (HCC), which has commonly a dismal prognosis. This study aimed to develop a multitask deep learning radiomics (MDLR) model for predicting MTM and HCC patie...

DeepHistoNet: A robust deep-learning model for the classification of hepatocellular, lung, and colon carcinoma.

Microscopy research and technique
In recent days, non-communicable diseases (NCDs) require more attention since they require specialized infrastructure for treatment. As per the cancer population registry estimate, nearly 800,000 new cancer cases will be detected yearly. The statisti...

MRI-Based Radiomics and Deep Learning in Biological Characteristics and Prognosis of Hepatocellular Carcinoma: Opportunities and Challenges.

Journal of magnetic resonance imaging : JMRI
Hepatocellular carcinoma (HCC) is the fifth most common malignancy and the third leading cause of cancer-related death worldwide. HCC exhibits strong inter-tumor heterogeneity, with different biological characteristics closely associated with prognos...

Prognostic role of computed tomography analysis using deep learning algorithm in patients with chronic hepatitis B viral infection.

Clinical and molecular hepatology
BACKGROUND/AIMS: The prediction of clinical outcomes in patients with chronic hepatitis B (CHB) is paramount for effective management. This study aimed to evaluate the prognostic value of computed tomography (CT) analysis using deep learning algorith...

Minimally Invasive Robotic Techniques for Hepatocellular Carcinoma Resection: How I Do It.

Surgical oncology clinics of North America
The adoption of minimally invasive techniques for hepatocellular resection has progressively increased in North America. Cumulative evidence has demonstrated improved surgical outcomes in patients who undergo minimally invasive hepatectomy. In this r...

Automatic prediction of hepatic arterial infusion chemotherapy response in advanced hepatocellular carcinoma with deep learning radiomic nomogram.

European radiology
OBJECTIVES: Hepatic arterial infusion chemotherapy (HAIC) using the FOLFOX regimen (oxaliplatin plus fluorouracil and leucovorin) is a promising option for advanced hepatocellular carcinoma (Ad-HCC). As identifying patients with Ad-HCC who would obta...

Deep learning-assisted LI-RADS grading and distinguishing hepatocellular carcinoma (HCC) from non-HCC based on multiphase CT: a two-center study.

European radiology
OBJECTIVES: To develop a deep learning (DL) method that can determine the Liver Imaging Reporting and Data System (LI-RADS) grading of high-risk liver lesions and distinguish hepatocellular carcinoma (HCC) from non-HCC based on multiphase CT.

Robot-Assisted Transarterial Chemoembolization of Hepatocellular Carcinoma Using a Coaxial Microcatheter Driving Controller-Responder Robot System: Clinical Pilot Study.

Journal of vascular and interventional radiology : JVIR
PURPOSE: To evaluate the feasibility and safety of robot-assisted transarterial chemoembolization (TACE) for hepatocellular carcinoma (HCC) using a new coaxial microcatheter driving controller-responder robot (CRR) system.