AIMC Topic: Liver
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GraftIQ: Hybrid multi-class neural network integrating clinical insight for multi-outcome prediction in liver transplant recipients.
Nature communications
May 28, 2025
Liver transplant recipients (LTRs) are at risk of graft injury, leading to cirrhosis and reduced survival. Liver biopsy, the diagnostic gold standard, is invasive and risky. We developed a hybrid multi-class neural network (NN) model, 'GraftIQ,' inte...
Identifying shared hub genes in LIRI and MASLD through bioinformatics analysis and machine learning.
Scientific reports
May 27, 2025
Patients with metabolic dysfunction-associated steatotic liver disease (MASLD) are more susceptible to liver ischemia-reperfusion injury (LIRI), complicating liver surgery outcomes. This study aimed to uncover shared hub genes and mechanisms linking ...
Machine Learning on Toxicogenomic Data Reveals a Strong Association Between the Induction of Drug-Metabolizing Enzymes and Centrilobular Hepatocyte Hypertrophy in Rats.
International journal of molecular sciences
May 20, 2025
Centrilobular hepatocyte hypertrophy is frequently observed in animal studies for chemical safety assessment. Although its toxicological significance and precise mechanism remain unknown, it is considered an adaptive response resulting from the induc...
Bioimpedance assessment method based on back propagation neural network for irreversible electroporation of liver tissue.
Scientific reports
May 8, 2025
The safety and efficacy of irreversible electroporation (IRE) in tumor therapy has been validated over many years by clinical application. An in-depth study, however, is required to assess the degree of ablation during the clinical dissemination of t...
Predicting adenine base editing efficiencies in different cellular contexts by deep learning.
Genome biology
May 8, 2025
BACKGROUND: Adenine base editors (ABEs) enable the conversion of A•T to G•C base pairs. Since the sequence of the target locus influences base editing efficiency, efforts have been made to develop computational models that can predict base editing ou...
Multiple machine learning algorithms identify 13 types of cell death-critical genes in large and multiple non-alcoholic steatohepatitis cohorts.
Lipids in health and disease
May 8, 2025
BACKGROUND: Dysregulated programmed cell death pathways mechanistically contribute to hepatic inflammation and fibrogenesis in non-alcoholic steatohepatitis (NASH). Identification of cell death genes may offer insights into diagnostic and therapeutic...
Interactive Explainable Deep Learning Model for Hepatocellular Carcinoma Diagnosis at Gadoxetic Acid-enhanced MRI: A Retrospective, Multicenter, Diagnostic Study.
Radiology. Imaging cancer
May 1, 2025
Purpose To develop an artificial intelligence (AI) model based on gadoxetic acid-enhanced MRI to assist radiologists in hepatocellular carcinoma (HCC) diagnosis. Materials and Methods This retrospective study included patients with focal liver lesion...
AI-augmented reconstruction provides improved image quality and enables shorter breath-holds in contrast-enhanced liver MRI.
European radiology experimental
May 1, 2025
BACKGROUND: To compare liver image quality and lesion detection using an AI-augmented T1-weighted sequence on hepatobiliary-phase gadoxetate-enhanced magnetic resonance imaging (MRI).
Utility of AI digital pathology as an aid for pathologists scoring fibrosis in MASH.
Journal of hepatology
May 1, 2025
BACKGROUND & AIMS: Intra and inter-pathologist variability poses a significant challenge in metabolic dysfunction-associated steatohepatitis (MASH) biopsy evaluation, leading to suboptimal selection of patients and confounded assessment of histologic...
Radiomics-based automated machine learning for differentiating focal liver lesions on unenhanced computed tomography.
Abdominal radiology (New York)
May 1, 2025
BACKGROUND & AIMS: Enhanced computed tomography (CT) is the primary method for focal liver lesion diagnosis. We aimed to use automated machine learning (AutoML) algorithms to differentiate between benign and malignant focal liver lesions on the basis...
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