AIMC Topic: Carcinoma, Hepatocellular

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Unveiling key drivers of hepatocellular carcinoma: a synergistic approach with network pharmacology, machine learning-driven ligand discovery and dynamic simulations.

SAR and QSAR in environmental research
Hepatocellular carcinoma (HCC) ranks fourth in cancer-related mortality worldwide. This study aims to uncover the genes and pathways involved in HCC through network pharmacology (NP) and to discover potential drugs via machine learning (ML)-based lig...

Machine Learning-Based Pathomics Model Predicts Angiopoietin-2 Expression and Prognosis in Hepatocellular Carcinoma.

The American journal of pathology
Angiopoietin-2 (ANGPT2) shows promise as prognostic marker and therapeutic target in hepatocellular carcinoma (HCC). However, assessing ANGPT2 expression and prognostic potential using histopathology images viewed with naked eye is challenging. Herei...

Construction of a random survival forest model based on a machine learning algorithm to predict early recurrence after hepatectomy for adult hepatocellular carcinoma.

BMC cancer
BACKGROUND AND AIMS: Hepatocellular carcinoma (HCC) exhibits a propensity for early recurrence following liver resection, resulting in a bleak prognosis. At present, majority of the predictive models for the early postoperative recurrence of HCC rely...

Artificial Intelligence and Machine Learning Predicting Transarterial Chemoembolization Outcomes: A Systematic Review.

Digestive diseases and sciences
BACKGROUND: Major society guidelines recommend transarterial chemoembolization (TACE) as the standard of care for intermediate-stage hepatocellular carcinoma (HCC) patients. However, predicting treatment response remains challenging.

AI model using CT-based imaging biomarkers to predict hepatocellular carcinoma in patients with chronic hepatitis B.

Journal of hepatology
BACKGROUND & AIMS: Various hepatocellular carcinoma (HCC) prediction models have been proposed for patients with chronic hepatitis B (CHB) using clinical variables. We aimed to develop an artificial intelligence (AI)-based HCC prediction model by inc...

Machine learning based prediction model for bile leak following hepatectomy for liver cancer.

HPB : the official journal of the International Hepato Pancreato Biliary Association
OBJECTIVE: We sought to develop a machine learning (ML) preoperative model to predict bile leak following hepatectomy for primary and secondary liver cancer.

A Machine Learning Model to Predict De Novo Hepatocellular Carcinoma Beyond Year 5 of Antiviral Therapy in Patients With Chronic Hepatitis B.

Liver international : official journal of the International Association for the Study of the Liver
BACKGROUND AND AIMS: This study aims to develop and validate a machine learning (ML) model predicting hepatocellular carcinoma (HCC) in chronic hepatitis B (CHB) patients after the first 5 years of entecavir (ETV) or tenofovir (TFV) therapy.

Targeting liver cancer stem cells: the prognostic significance of MRPL17 in immunotherapy response.

Frontiers in immunology
BACKGROUND: Liver hepatocellular carcinoma (LIHC) ranks as the foremost cause of cancer-related deaths worldwide, and its early detection poses considerable challenges. Current prognostic indicators, including alpha-fetoprotein, have notable limitati...

Machine learning and multi-omics characterization of SLC2A1 as a prognostic factor in hepatocellular carcinoma: SLC2A1 is a prognostic factor in HCC.

Gene
Hepatocellular carcinoma (HCC) is characterized by high incidence, significant mortality, and marked heterogeneity, making accurate molecular subtyping essential for effective treatment. Using multi-omics data from HCC patients, we applied diverse cl...

Comparison between two artificial intelligence models to discriminate cancerous cell nuclei based on confocal fluorescence imaging in hepatocellular carcinoma.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
BACKGROUND: Hepatocellular carcinoma (HCC) exhibits an exceptional intratumoral heterogeneity that might influence diagnosis and outcome. Advances in digital microscopy and artificial intelligence (AI) may improve the HCC identification of liver canc...