AIMC Topic: Liver Diseases

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Artificial Intelligence in Imaging of Chronic Liver Diseases: Current Update and Future Perspectives.

Magnetic resonance imaging clinics of North America
Here we review artificial intelligence (AI) models which aim to assess various aspects of chronic liver disease. Despite the clinical importance of hepatocellular carcinoma in the setting of chronic liver disease, we focus this review on AI models wh...

Application of Artificial Intelligence for the Diagnosis and Treatment of Liver Diseases.

Hepatology (Baltimore, Md.)
Modern medical care produces large volumes of multimodal patient data, which many clinicians struggle to process and synthesize into actionable knowledge. In recent years, artificial intelligence (AI) has emerged as an effective tool in this regard. ...

Radiomics and deep learning in liver diseases.

Journal of gastroenterology and hepatology
Recently, radiomics and deep learning have gained attention as methods for computerized image analysis. Radiomics and deep learning can perform diagnostic or predictive tasks using high-dimensional image-derived features and have the potential to exp...

Artificial intelligence in precision medicine in hepatology.

Journal of gastroenterology and hepatology
The advancement of investigation tools and electronic health records (EHR) enables a paradigm shift from guideline-specific therapy toward patient-specific precision medicine. The multiparametric and large detailed information necessitates novel anal...

Artificial intelligence in liver disease.

Journal of gastroenterology and hepatology
Artificial intelligence (AI) is a branch of computer science that attempts to mimic human intelligence, such as learning and problem-solving skills. The use of AI in hepatology occurred later than in gastroenterology. Nevertheless, studies on applyin...

Expert-level segmentation using deep learning for volumetry of polycystic kidney and liver.

Investigative and clinical urology
PURPOSE: Volumetry is used in polycystic kidney and liver diseases (PKLDs), including autosomal dominant polycystic kidney disease (ADPKD), to assess disease progression and drug efficiency. However, since no rapid and accurate method for volumetry h...

Deep Learning Algorithm for Automated Segmentation and Volume Measurement of the Liver and Spleen Using Portal Venous Phase Computed Tomography Images.

Korean journal of radiology
OBJECTIVE: Measurement of the liver and spleen volumes has clinical implications. Although computed tomography (CT) volumetry is considered to be the most reliable noninvasive method for liver and spleen volume measurement, it has limited application...

Ontologies for Liver Diseases Representation: A Systematic Literature Review.

Journal of digital imaging
Ontology, as a useful knowledge engineering technique, has been widely used for reducing ambiguity and helping with information sharing. It is considered originally to be clear, comprehensive, and with well-defined format. It characterizes several do...

Radiomics and Deep Learning: Hepatic Applications.

Korean journal of radiology
Radiomics and deep learning have recently gained attention in the imaging assessment of various liver diseases. Recent research has demonstrated the potential utility of radiomics and deep learning in staging liver fibroses, detecting portal hyperten...