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Hepatocellular carcinoma [PDF]

open access: yesNature Reviews Disease Primers, 2021
Liver cancer remains a global health challenge, with an estimated incidence of1 million cases by 2025. Hepatocellular carcinoma (HCC) is the most common form of liver cancer and accounts for ~90% of cases. Infection by hepatitis B virus and hepatitis C virus are the main risk factors for HCC development, although non-alcoholic steatohepatitis ...
Llovet, Josep M.   +9 more
semanticscholar   +6 more sources

Hepatocellular carcinoma [PDF]

open access: yesNature Reviews Disease Primers, 2016
Liver cancer is the second leading cause of cancer-related deaths globally and has an incidence of approximately 850,000 new cases per year. Hepatocellular carcinoma (HCC) represents approximately 90% of all cases of primary liver cancer. The main risk factors for developing HCC are well known and include hepatitis B and C virus infection, alcohol ...
Llovet, Josep M.   +6 more
  +9 more sources

Hepatocellular carcinoma [PDF]

open access: yesBritish Journal of Cancer, 2001
The number of papers published regarding hepatocellular carcinoma between 1999 and 2001 increased from previous years. This year a study confirmed the increase in incidence in the United States. Also, several studies established for the first time that tobacco smoking was a risk factor for the development of this tumor. Several studies established that
Giovannini, M   +4 more
openaire   +4 more sources

Hepatocellular carcinoma

open access: yesJournal of British Surgery, 1998
Abstract Background Hepatocellular carcinoma is one of the world's most common malignancies. The aims of the present paper are to review data on (1) epidemiology and screening programmes for the early detection of the tumour and (2) advances in the diagnostic imaging and management.
Akriviadis, E. A.   +6 more
openaire   +5 more sources

Multi-Instance Multi-Label Learning for Gene Mutation Prediction in Hepatocellular Carcinoma [PDF]

open access: yes2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2020
Gene mutation prediction in hepatocellular carcinoma (HCC) is of great diagnostic and prognostic value for personalized treatments and precision medicine. In this paper, we tackle this problem with multi-instance multi-label learning to address the difficulties on label correlations, label representations, etc.
arxiv   +1 more source

Edge-competing Pathological Liver Vessel Segmentation with Limited Labels [PDF]

open access: yesarXiv, 2021
The microvascular invasion (MVI) is a major prognostic factor in hepatocellular carcinoma, which is one of the malignant tumors with the highest mortality rate. The diagnosis of MVI needs discovering the vessels that contain hepatocellular carcinoma cells and counting their number in each vessel, which depends heavily on experiences of the doctor, is ...
arxiv  

Multi-Phase Cross-modal Learning for Noninvasive Gene Mutation Prediction in Hepatocellular Carcinoma [PDF]

open access: yes2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2020
Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and the fourth most common cause of cancer-related death worldwide. Understanding the underlying gene mutations in HCC provides great prognostic value for treatment planning and targeted therapy. Radiogenomics has revealed an association between non-invasive imaging features
arxiv   +1 more source

Prevention of hepatocellular carcinoma [PDF]

open access: yesAnnals of Hepatology, 2005
Because of its frequency and grave prognosis, preventing hepatocellular carcinoma is an urgent priority. Prevention should be possible because environmental carcinogens-chronic hepatitis B and C virus infections, dietary exposure to aflatoxins, and iron overload-cause the great majority of these tumors.
openaire   +9 more sources

Leveraging weak complementary labels to improve semantic segmentation of hepatocellular carcinoma and cholangiocarcinoma in H&E-stained slides [PDF]

open access: yesarXiv, 2023
In this paper, we present a deep learning segmentation approach to classify and quantify the two most prevalent primary liver cancers - hepatocellular carcinoma and intrahepatic cholangiocarcinoma - from hematoxylin and eosin (H&E) stained whole slide images.
arxiv  

Hepatocellular Carcinoma Segmentation from Digital Subtraction Angiography Videos using Learnable Temporal Difference [PDF]

open access: yesarXiv, 2021
Automatic segmentation of hepatocellular carcinoma (HCC) in Digital Subtraction Angiography (DSA) videos can assist radiologists in efficient diagnosis of HCC and accurate evaluation of tumors in clinical practice. Few studies have investigated HCC segmentation from DSA videos.
arxiv  

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