AIMC Topic: Liver

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Identification of key factors and explainability analysis for surgical decision-making in hepatic alveolar echinococcosis assisted by machine learning.

World journal of gastroenterology
BACKGROUND: Echinococcosis, caused by Echinococcus parasites, includes alveolar echinococcosis (AE), the most lethal form, primarily affecting the liver with a 90% mortality rate without prompt treatment. While radical surgery combined with antiparas...

Downregulation of HDAC9 Alleviates Autophagy Dysfunction by Inducing Acetylation of ATG4B in Metabolic Dysfunction-Associated Steatotic Liver Disease.

FASEB journal : official publication of the Federation of American Societies for Experimental Biology
Metabolic dysfunction-associated steatotic liver disease (MASLD) is a prevalent hepatic metabolic disorder with a rising global incidence. Epigenetic modifications-such as methylation, acetylation, phosphorylation, and ubiquitination-play critical ro...

Development of AI Based Fibrosis Detection Algorithm by SHG/TPEF Microscopy for Fully Quantified Liver Fibrosis Assessment in MASH.

Liver international : official journal of the International Association for the Study of the Liver
BACKGROUND AND AIMS: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a major global cause of chronic liver disease, with the potential to progress from steatosis to metabolic dysfunction-associated steatohepatitis (MASH) and cirrh...

Signature gene expression model for quantitative evaluation of MASH-like liver injury in mice.

Toxicology and applied pharmacology
Metabolic dysfunction-associated steatotic liver disease (MASLD) is a spectrum of chronic pathologic conditions strongly associated with metabolic syndrome and affects approximately 38 % of the global population. Untreated MASLD may progress to metab...

Estimation of postmortem interval under different ambient temperatures based on multi-organ metabolomics and machine learning algorithm.

International journal of legal medicine
In forensic practice, the estimation of postmortem interval has been a persistent challenge. Recently, there has been an increasing utilization of metabolomics techniques combined with machine learning methods for postmortem interval estimation. When...

Predicting in vitro assays related to liver function using probabilistic machine learning.

Toxicology
While machine learning has gained traction in toxicological assessments, the limited data availability requires the quantification of uncertainty of in silico predictions for reliable decision-making. This study addresses the challenge of predicting ...

CDKN1A and EGR1 are key genes for endoplasmic reticulum stress-induced ferroptosis in MASH.

Free radical biology & medicine
Metabolic dysfunction-associated steatohepatitis (MASH) is a complex liver disease whose pathogenesis involving endoplasmic reticulum (ER) stress and ferroptosis. However, key regulatory genes remain poorly understood, hindering the development of ef...

Enhancing HF-DL Model Validation for Liver Fibrosis Staging Through Sample Optimisation and Technical Integration.

Liver international : official journal of the International Association for the Study of the Liver
We read with great interest the article by Zhang et al. The study demonstrates that the deep learning model based on high-frequency ultrasound images significantly outperforms the low-frequency ultrasound model, FIB-4, APRI, and shear wave elastograp...

Digital Pathology Quantification of the Continuum of Cirrhosis Severity in Human Liver Biopsies.

Liver international : official journal of the International Association for the Study of the Liver
BACKGROUND AND AIMS: Liver biopsy is the gold standard for assessing fibrosis in cirrhotic livers, yet cirrhosis is spatially heterogeneous and continuously remodels. This study evaluates a novel phenotypic digital pathology platform for continuous f...

A Deep Learning Model Based on High-Frequency Ultrasound Images for Classification of Different Stages of Liver Fibrosis.

Liver international : official journal of the International Association for the Study of the Liver
BACKGROUND AND AIMS: To develop a deep learning model based on high-frequency ultrasound images to classify different stages of liver fibrosis in chronic hepatitis B patients.