AIMC Topic: Carcinoma, Hepatocellular

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Resolution-Adaptive Binning Enhances Machine Learning Modeling by Interbatch and Multiplatform Orbitrap-Based Shotgun Mass Spectrometry Data Integration.

Analytical chemistry
Machine learning (ML) modeling on mass spectrometry (MS)-based shotgun data facilitates feature selection and disease modeling. However, batch-specific models often struggle with limited transferability and generalizability, necessitating data integr...

Deep learning for automatic segmentation of hepatocellular carcinoma in contrast enhanced CT scans.

Scientific reports
Liver cancer represents a significant cause of cancer-related mortality, with hepatocellular carcinoma (HCC) being the most prevalent forms. Computed tomography (CT) serves as the principal imaging modality for the diagnosis of liver tumors, particul...

MRI-based 2.5D deep learning and radiomics effectively predicted microvascular invasion and Ki-67 expression in hepatocellular carcinoma.

PloS one
OBJECTIVE: To develop and validate an integrated 2.5D deep learning (DL) and Radiomics model using gadoxetic acid-enhanced MRI hepatobiliary phase (HBP) images combined with clinical features for preoperative prediction of microvascular invasion (MVI...

Synergistic approach utilizing bioinformatics, machine learning, and traditional screening for the identification of novel CSK inhibitors targeting hepatocellular carcinoma.

Journal of computer-aided molecular design
The overexpression or activation of C-terminal Src kinase (CSK) has been recognized as a pivotal factor in the progression of hepatocellular carcinoma (HCC), positioning CSK as a promising therapeutic target. Despite this potential, no CSK-specific i...

Preoperative plasma ceramide profiling coupled with machine learning accurately predicts recurrence of hepatocellular carcinoma after resection.

Lipids in health and disease
BACKGROUND: Accurate stratification of recurrence risk after curative resection remains a critical challenge in the management of hepatocellular carcinoma (HCC). Dysregulated ceramide (CER) metabolism has been implicated in HCC progression and relaps...

GlyTrait: A Versatile Bioinformatics Tool for Glycomics Analysis.

Journal of proteome research
We developed GlyTrait, a Python-based framework designed to enhance Glycomics analysis through the innovative calculation and interpretation of derived traits from -glycome data. Glycomics research often grapples with the interpretability and biologi...

Characterizing immune profiles in hepatocellular carcinoma patients benefiting from pembrolizumab and lenvatinib using machine learning.

BMC cancer
BACKGROUND: Combination immunotherapies, such as pembrolizumab plus lenvatinib (PL), are commonly used in treatment for unresectable hepatocellular carcinoma (uHCC). However, it remains challenging to predict which patients will benefit from this the...

Programmed cell death-related genes define distinct molecular subtypes and risk profiles in hepatocellular carcinoma.

Scientific reports
Hepatocellular carcinoma (HCC) is a biologically and clinically heterogeneous malignancy, whose initiation and progression are increasingly recognized to be driven by the aberrant regulation of programmed cell death (PCD) pathways. To elucidate this ...

Deep multi-instance learning model based on gadoxetic acid-enhanced MRI for predicting microvascular invasion of hepatocellular carcinoma: a multicenter, retrospective study.

BMC cancer
OBJECTIVE: Microvascular invasion (MVI) is of great significance for the individualized treatment of hepatocellular carcinoma (HCC) and preoperative noninvasive prediction of MVI is still an urgent clinical problem. To explore the effects of differen...

Development and Validation of an Extra Spindle Pole Bodies-like 1-Based Diagnostic and Prognostic Model for Hepatitis B Virus-Related Hepatocellular Carcinoma: Retrospective Cohort Study.

JMIR medical informatics
BACKGROUND: Early diagnosis of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B virus (HBV) is challenging. Models that combine novel biomarkers with clinical features may improve both early diagnosis and risk stratification, but f...