AIMC Topic: Fatty Liver

Clear Filters Showing 41 to 50 of 94 articles

A natural language processing algorithm accurately classifies steatotic liver disease pathology to estimate the risk of cirrhosis.

Hepatology communications
BACKGROUND: Histopathology remains the gold standard for diagnosing and staging metabolic dysfunction-associated steatotic liver disease (MASLD). The feasibility of studying MASLD progression in electronic medical records based on histological featur...

Fatty liver classification via risk controlled neural networks trained on grouped ultrasound image data.

Scientific reports
Ultrasound imaging is a widely used technique for fatty liver diagnosis as it is practically affordable and can be quickly deployed by using suitable devices. When it is applied to a patient, multiple images of the targeted tissues are produced. We p...

Early and accurate diagnosis of steatotic liver by artificial intelligence (AI)-supported ultrasonography.

European journal of internal medicine
OBJECTIVES: Steatotic liver disease is the most frequent chronic liver disease worldwide. Ultrasonography (US) is commonly employed for the assessment and diagnosis. Few information is available on the possible use of artificial intelligence (AI) to ...

Digital pathology with artificial intelligence analysis provides insight to the efficacy of anti-fibrotic compounds in human 3D MASH model.

Scientific reports
Metabolic dysfunction-associated steatohepatitis (MASH) is a severe liver disease characterized by lipid accumulation, inflammation and fibrosis. The development of MASH therapies has been hindered by the lack of human translational models and limita...

Image-based AI diagnostic performance for fatty liver: a systematic review and meta-analysis.

BMC medical imaging
BACKGROUND: The gold standard to diagnose fatty liver is pathology. Recently, image-based artificial intelligence (AI) has been found to have high diagnostic performance. We systematically reviewed studies of image-based AI in the diagnosis of fatty ...

A novel multi-feature learning model for disease diagnosis using face skin images.

Computers in biology and medicine
BACKGROUND: Facial skin characteristics can provide valuable information about a patient's underlying health conditions.

Improved assessment of donor liver steatosis using Banff consensus recommendations and deep learning algorithms.

Journal of hepatology
BACKGROUND & AIMS: The Banff Liver Working Group recently published consensus recommendations for steatosis assessment in donor liver biopsy, but few studies reported their use and no automated deep-learning algorithms based on the proposed criteria ...

Deep Learning-Based Survival Analysis for Receiving a Steatotic Donor Liver Versus Waiting for a Standard Liver.

Transplantation proceedings
BACKGROUND: An emerging strategy to expand the donor pool is the use of a steatotic donor liver (SDLs; ≥ 30% macrosteatosis on biopsy). With the obesity epidemic and prevalence of nonalcoholic fatty liver disease, SDLs have been reported in 59% of al...