AIMC Topic: Liver Neoplasms

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Serum peptide biomarkers by MALDI-TOF MS coupled with machine learning for diagnosis and classification of hepato-pancreato-biliary cancers.

Scientific reports
This study aimed to investigate the potential of peptide mass fingerprints (PMFs) of the serum peptidome using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), in combination with machine learning algorithm...

Early prediction of proton therapy dose distributions and DVHs for hepatocellular carcinoma using contour-based CNN models from diagnostic CT and MRI.

Radiation oncology (London, England)
BACKGROUND: Proton therapy is commonly used for treating hepatocellular carcinoma (HCC); however, its feasibility can be challenging to assess in large tumors or those adjacent to critical organs at risk (OARs), which are typically assessed only afte...

Evaluating the efficacy of using large language models in preoperative prediction of microvascular invasion in HCC: a multicenter study.

Scientific reports
Primary liver cancer is the sixth most commonly diagnosed cancer globally and the third leading cause of cancer-related deaths. Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer, and microvascular invasion (MVI) is a sign...

Integrated multi-omics analysis and machine learning refine molecular subtypes and prognosis in hepatocellular carcinoma through O-linked glycosylation genes.

Functional & integrative genomics
O-glycosylation significantly influences cellular physiological processes and disease regulation by modulating the structure, function, and stability of proteins. However, there is a notable gap in research focusing on O-glycosylation in relation to ...

Integrating bulk and single cell sequencing data to identify prognostic biomarkers and drug candidates in HBV associated hepatocellular carcinoma.

Scientific reports
Hepatitis B virus (HBV) infection is a major driver of hepatocellular carcinoma (HCC), yet the mechanisms by which HBV triggers HCC and how it interacts with the immune system remain largely undefined. In this study, 53 immune-related key genes invol...

FSS-ULivR: a clinically-inspired few-shot segmentation framework for liver imaging using unified representations and attention mechanisms.

Journal of cancer research and clinical oncology
Precise liver segmentation is critical for accurate diagnosis and effective treatment planning, serving as a foundation for medical image analysis. However, existing methods struggle with limited labeled data, poor generalizability, and insufficient ...

Cost-effectiveness analysis of artificial intelligence (AI) in earlier detection of liver lesions in cirrhotic patients at risk of hepatocellular carcinoma in Italy.

Journal of medical economics
BACKGROUND: Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide and the third most common cause of cancer-related death. Cirrhosis is a major contributing factor, accounting for over 90% of HCC cases. With the high mortality rate...

SPP1 promotes malignant characteristics and drug resistance in hepatocellular carcinoma by activating fatty acid metabolic pathway.

Functional & integrative genomics
Hepatocellular carcinoma (HCC) progression and prognosis are influenced by various molecular markers. This study aimed to identify the hub gene associated with HCC clinical characteristics and its role in HCC progression. Differentially expressed gen...

The unwell patient with advanced chronic liver disease: when to use each score?

BMC medicine
BACKGROUND: Prognostication in chronic liver disease and the implementation of appropriate scoring systems is difficult given the variety of clinical manifestations. It is important to understand the limitations of each scoring system as well as the ...

Machine learning models using non-invasive tests & B-mode ultrasound to predict liver-related outcomes in metabolic dysfunction-associated steatotic liver disease.

Scientific reports
Advanced metabolic-dysfunction-associated steatotic liver disease (MASLD) fibrosis (F3-4) predicts liver-related outcomes. Serum and elastography-based non-invasive tests (NIT) cannot yet reliably predict MASLD outcomes. The role of B-mode ultrasound...