The role of artificial intelligence in the detection and implementation of biomarkers for hepatocellular carcinoma: outlook and opportunities

A Mansur, A Vrionis, JP Charles, K Hancel… - Cancers, 2023 - mdpi.com
Simple Summary Liver cancer is a major health problem worldwide, and its early detection
and management are imperative for improving patient outcomes. Biomarkers have great …

A hybrid dipper throated optimization algorithm and particle swarm optimization (DTPSO) model for hepatocellular carcinoma (HCC) prediction

MY Shams, ESM El-Kenawy, A Ibrahim… - … Signal Processing and …, 2023 - Elsevier
Hepatocellular carcinoma (HCC) is a form of liver cancer that is widespread in Europe,
Africa, and Asia. The early identification of HCC is critical in improving the likelihood of …

The role of radiomics and AI technologies in the segmentation, detection, and management of hepatocellular carcinoma

D Fahmy, A Alksas, A Elnakib, A Mahmoud, H Kandil… - Cancers, 2022 - mdpi.com
Simple Summary As a primary hepatic tumor, hepatocellular carcinoma (HCC) is the most
prevalent kind. Recent developments in magnetic resonance imaging (MRI) and computed …

[HTML][HTML] Evolutionary learning-derived clinical-radiomic models for predicting early recurrence of hepatocellular carcinoma after resection

I Lee, JY Huang, TC Chen, CH Yen, NC Chiu… - Liver cancer, 2021 - karger.com
Abstract Background and Aims: Current prediction models for early recurrence of
hepatocellular carcinoma (HCC) after surgical resection remain unsatisfactory. The aim of …

The emerging factors and treatment options for NAFLD-related hepatocellular carcinoma

C Zhang, M Yang - Cancers, 2021 - mdpi.com
Simple Summary Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver
disease, and it is an increasing factor in the cause of hepatocellular carcinoma (HCC). The …

A primer on texture analysis in abdominal radiology

N Horvat, J Miranda, M El Homsi, JJ Peoples… - Abdominal …, 2022 - Springer
The number of publications on texture analysis (TA), radiomics, and radiogenomics has
been growing exponentially, with abdominal radiologists aiming to build new prognostic or …

Artificial intelligence in the era of precision oncological imaging

M Cellina, M Cè, N Khenkina… - … in Cancer Research …, 2022 - journals.sagepub.com
Rapid-paced development and adaptability of artificial intelligence algorithms have secured
their almost ubiquitous presence in the field of oncological imaging. Artificial intelligence …

A review of the clinical applications of artificial intelligence in abdominal imaging

BM Mervak, JG Fried, AP Wasnik - Diagnostics, 2023 - mdpi.com
Artificial intelligence (AI) has been a topic of substantial interest for radiologists in recent
years. Although many of the first clinical applications were in the neuro, cardiothoracic, and …

Imaging of pediatric liver tumors: a COG diagnostic imaging committee/SPR oncology committee white paper

GR Schooler, JC Infante, M Acord… - Pediatric blood & …, 2023 - Wiley Online Library
Primary hepatic malignancies are relatively rare in the pediatric population, accounting for
approximately 1%–2% of all pediatric tumors. Hepatoblastoma and hepatocellular …

A hierarchical fusion strategy of deep learning networks for detection and segmentation of hepatocellular carcinoma from computed tomography images

IC Lee, YP Tsai, YC Lin, TC Chen, CH Yen, NC Chiu… - Cancer Imaging, 2024 - Springer
Background Automatic segmentation of hepatocellular carcinoma (HCC) on computed
tomography (CT) scans is in urgent need to assist diagnosis and radiomics analysis. The …