AIMC Topic: Carcinoma, Hepatocellular

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Study of prognostic splicing factors in cancer using machine learning approaches.

Human molecular genetics
Splicing factors (SFs) are the major RNA-binding proteins (RBPs) and key molecules that regulate the splicing of mRNA molecules through binding to mRNAs. The expression of splicing factors is frequently deregulated in different cancer types, causing ...

A clinical-radiomic-pathomic model for prognosis prediction in patients with hepatocellular carcinoma after radical resection.

Cancer medicine
PURPOSE: Radical surgery, the first-line treatment for patients with hepatocellular cancer (HCC), faces the dilemma of high early recurrence rates and the inability to predict effectively. We aim to develop and validate a multimodal model combining c...

Prognostication of Hepatocellular Carcinoma Using Artificial Intelligence.

Korean journal of radiology
Hepatocellular carcinoma (HCC) is a biologically heterogeneous tumor characterized by varying degrees of aggressiveness. The current treatment strategy for HCC is predominantly determined by the overall tumor burden, and does not address the diverse ...

Feasibility and safety of robotic liver resection for huge (≥10 cm) hepatocellular carcinoma in a single centre: A propensity score-matched single-surgeon study.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: The applicability of robot-assisted resection for huge hepatocellular carcinoma (HCC) of ≥10 cm remains contentious with limited available data.

Deep learning-based accurate diagnosis and quantitative evaluation of microvascular invasion in hepatocellular carcinoma on whole-slide histopathology images.

Cancer medicine
BACKGROUND: Microvascular invasion (MVI) is an independent prognostic factor that is associated with early recurrence and poor survival after resection of hepatocellular carcinoma (HCC). However, the traditional pathology approach is relatively subje...

Image Quality and Diagnostic Performance of Low-Dose Liver CT with Deep Learning Reconstruction versus Standard-Dose CT.

Radiology. Artificial intelligence
Purpose To compare the image quality and diagnostic capability in detecting malignant liver tumors of low-dose CT (LDCT, 33% dose) with deep learning-based denoising (DLD) and standard-dose CT (SDCT, 100% dose) with model-based iterative reconstructi...

Whole-Liver Based Deep Learning for Preoperatively Predicting Overall Survival in Patients with Hepatocellular Carcinoma.

Studies in health technology and informatics
Survival prediction is crucial for treatment decision making in hepatocellular carcinoma (HCC). We aimed to build a fully automated artificial intelligence system (FAIS) that mines whole-liver information to predict overall survival of HCC. We includ...

Deep learning-based radiomics allows for a more accurate assessment of sarcopenia as a prognostic factor in hepatocellular carcinoma.

Journal of Zhejiang University. Science. B
Hepatocellular carcinoma (HCC) is one of the most common malignancies and is a major cause of cancer-related mortalities worldwide (Forner et al., 2018; He et al., 2023). Sarcopenia is a syndrome characterized by an accelerated loss of skeletal muscl...