AIMC Topic: Carcinoma, Hepatocellular

Clear Filters Showing 401 to 410 of 452 articles

Harnessing the Power of AI for Enhanced Diagnosis and Treatment of Hepatocellular Carcinoma.

The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology
Since its advent, artificial intelligence (AI) has been continuously researched, and substantial progress has been made in many fields, such as the diagnosis and therapies for cancer. Due to the advantages of high efficiency, rapidity, and precision,...

A transformer-based deep learning survival prediction model and an explainable XGBoost anti-PD-1/PD-L1 outcome prediction model based on the cGAS-STING-centered pathways in hepatocellular carcinoma.

Briefings in bioinformatics
Recent studies suggest cGAS-STING pathway may play a crucial role in the genesis and development of hepatocellular carcinoma (HCC), closely associated with classical pathways and tumor immunity. We aimed to develop models predicting survival and anti...

Hepatocellular Carcinoma Immune Microenvironment Analysis: A Comprehensive Assessment with Computational and Classical Pathology.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: The spatial variability and clinical relevance of the tumor immune microenvironment (TIME) are still poorly understood for hepatocellular carcinoma (HCC). In this study, we aim to develop a deep learning (DL)-based image analysis model for t...

Review on article of preoperative prediction in chronic hepatitis B virus patients using spectral computed tomography and machine learning.

World journal of gastroenterology
This letter comments on the article that developed and tested a machine learning model that predicts lymphovascular invasion/perineural invasion status by combining clinical indications and spectral computed tomography characteristics accurately. We ...

Machine Learning Diagnostic Model for Hepatocellular Carcinoma Based on Liquid-Liquid Phase Separation and Ferroptosis-Related Genes.

The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology
BACKGROUND/AIMS: Hepatocellular carcinoma (HCC) represents a primary liver malignancy with a multifaceted molecular landscape. The interplay between liquid-liquid phase separation (LLPS) and ferroptosis-a regulated form of cell death-has garnered int...

[A deep learning model based on magnetic resonance imaging and clinical feature fusion for predicting preoperative cytokeratin 19 status in hepatocellular carcinoma].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University
OBJECTIVE: To establish a deep learning model for testing the feasibility of combining magnetic resonance imaging (MRI) deep learning features with clinical features for preoperative prediction of cytokeratin 19 (CK19) status of hepatocellular carcin...

Identification of novel M2 macrophage-related molecule ATP6V1E1 and its biological role in hepatocellular carcinoma based on machine learning algorithms.

Journal of cellular and molecular medicine
Hepatocellular carcinoma (HCC) remains the most prevalent form of primary liver cancer, characterized by late detection and suboptimal response to current therapies. The tumour microenvironment, especially the role of M2 macrophages, is pivotal in th...

Leveraging SEER data through machine learning to predict distant lymph node metastasis and prognosticate outcomes in hepatocellular carcinoma patients.

The journal of gene medicine
OBJECTIVES: This study aims to develop and validate machine learning-based diagnostic and prognostic models to predict the risk of distant lymph node metastases (DLNM) in patients with hepatocellular carcinoma (HCC) and to evaluate the prognosis for ...

Establishment of diagnostic model and identification of diagnostic markers between liver cancer and cirrhosis based on multi-chip and machine learning.

Clinical and experimental pharmacology & physiology
OBJECTIVE: Most cases of hepatocellular carcinoma (HCC) arise as a consequence of cirrhosis. In this study, our objective is to construct a comprehensive diagnostic model that investigates the diagnostic markers distinguishing between cirrhosis and H...

A Machine Learning Algorithm Facilitates Prognosis Prediction and Treatment Selection for Barcelona Clinic Liver Cancer Stage C Hepatocellular Carcinoma.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: Given its heterogeneity and diverse clinical outcomes, precise subclassification of Barcelona Clinic Liver Cancer stage C (BCLC-C) hepatocellular carcinoma (HCC) is required for appropriately determining patient prognosis and selecting treat...