AIMC Topic: Carcinoma, Hepatocellular

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Cell Segmentation With Globally Optimized Boundaries (CSGO): A Deep Learning Pipeline for Whole-Cell Segmentation in Hematoxylin-and-Eosin-Stained Tissues.

Laboratory investigation; a journal of technical methods and pathology
Accurate whole-cell segmentation is essential in various biomedical applications, particularly in studying the tumor microenvironment. Despite advancements in machine learning for nuclei segmentation in hematoxylin and eosin (H&E)-stained images, the...

A deep learning framework for hepatocellular carcinoma diagnosis using MS1 data.

Scientific reports
Clinical proteomics analysis is of great significance for analyzing pathological mechanisms and discovering disease-related biomarkers. Using computational methods to accurately predict disease types can effectively improve patient disease diagnosis ...

Managing Postembolization Syndrome Through a Machine Learning-Based Clinical Decision Support System: A Randomized Controlled Trial.

Computers, informatics, nursing : CIN
Although transarterial chemoembolization has improved as an interventional method for hepatocellular carcinoma, subsequent postembolization syndrome is a threat to the patients' quality of life. This study aimed to evaluate the effectiveness of a cli...

Decision Fusion Model for Predicting Microvascular Invasion in Hepatocellular Carcinoma Based on Multi-MR Habitat Imaging and Machine-Learning Classifiers.

Academic radiology
RATIONALE AND OBJECTIVES: Accurate prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) is crucial for guiding treatment. This study evaluates and compares the performance of clinicoradiologic, traditional radiomics, deep-lear...

Prediction of hepatocellular carcinoma response to radiation segmentectomy using an MRI-based machine learning approach.

Abdominal radiology (New York)
PURPOSE: To evaluate the value of pre-treatment MRI-based radiomics in patients with hepatocellular carcinoma (HCC) for the prediction of response to Yttrium 90 radiation segmentectomy.

The role of artificial intelligence in the management of liver diseases.

The Kaohsiung journal of medical sciences
Universal neonatal hepatitis B virus (HBV) vaccination and the advent of direct-acting antivirals (DAA) against hepatitis C virus (HCV) have reshaped the epidemiology of chronic liver diseases. However, some aspects of the management of chronic liver...

Machine learning identification of NK cell immune characteristics in hepatocellular carcinoma based on single-cell sequencing and bulk RNA sequencing.

Genes & genomics
BACKGROUND: Hepatocellular carcinoma (HCC) is a highly malignant tumor; however, its immune microenvironment and mechanisms remain elusive. Single-cell sequencing allows for the exploration of immune characteristics within tumor at the cellular level...

Integrating anoikis and ErbB signaling insights with machine learning and single-cell analysis for predicting prognosis and immune-targeted therapy outcomes in hepatocellular carcinoma.

Frontiers in immunology
BACKGROUND: Hepatocellular carcinoma (HCC) poses a significant global health challenge due to its poor prognosis and limited therapeutic modalities. Anoikis and ErbB signaling pathways are pivotal in cancer cell proliferation and metastasis, but thei...

Development of HepatIA: A computed tomography annotation platform and database for artificial intelligence training in hepatocellular carcinoma detection at a Brazilian tertiary teaching hospital.

Clinics (Sao Paulo, Brazil)
BACKGROUND: Hepatocellular carcinoma (HCC) is a prevalent tumor with high mortality rates. Computed tomography (CT) is crucial in the non-invasive diagnosis of HCC. Recent advancements in artificial intelligence (AI) have shown significant potential ...

A review of deep learning approaches for multimodal image segmentation of liver cancer.

Journal of applied clinical medical physics
This review examines the recent developments in deep learning (DL) techniques applied to multimodal fusion image segmentation for liver cancer. Hepatocellular carcinoma is a highly dangerous malignant tumor that requires accurate image segmentation f...