Liver Transplantation

Large Language Models for Heterogeneous Data Mining in Liver Disease: Framework Development and Retrospective Validation Study.

BACKGROUND: Differentiating among liver disease entities such as autoimmune liver disease (AILD), drug-induced liver injury (DILI), and chronic hepatitis B (CHB) remains clinically challenging due to overlapping clinical manifestations and nonspecific laboratory findings. Conventional machine learning (ML) approaches rely mainly on structured laboratory data, whereas free-text clinical reports and...

Machine Learning and Molecular Modeling Reveal HDAC6 as a Key Target of Tanshinone IIA in Multiple Myeloma.

Multiple myeloma (MM) is a malignant blood cancer marked by severe bone destruction and immune microenvironment disruption. Yet relapse and drug resistance remain major clinical challenges. Tanshinone IIA (TIIA) exhibits potent antitumor activity, but its molecular targets and mechanisms in MM remain unclear. Here, we systematically elucidate TIIA's pharmacological mechanisms in MM using network p...

Machine learning identifies ac4C-related prognostic signature and TUBA1C as therapeutic target in COAD.

To explore the role of N4-acetylcytidine (ac4C)-related genes (acRGs) in colon adenocarcinoma (COAD) and identify reliable prognostic biomarkers and p...

Targeting GLUTs in Cancer: Mechanisms, Combination Strategies, and Translational Challenges.

Cancer cells exhibit metabolic reprogramming, most notably the Warburg effect, which underscores their heightened dependency on glucose uptake facilit...

Cost-Effectiveness of AI-Enabled Electrocardiography for Screening MASLD-Associated Advanced Chronic Liver Disease in the US Population.

BACKGROUND: MASLD is the most prevalent chronic liver disease worldwide, with pooled global prevalence estimates of approximately 30%. Current noninva...

Machine learning models for early detection of urinary tract infections in kidney transplant patients.

BACKGROUND: Renal transplantation is the preferred treatment for end-stage chronic kidney disease but requires lifelong immunosuppression, increasing ...

Peptide Therapeutics for Solid Tumors: Functional Classes, AI-Enhanced Discovery and Clinical Advances.

Solid tumors, the most prevalent form of malignancy, pose therapeutic challenges distinct from hematologic malignancies due to their complex biology, ...

Identification of Pre-Diagnostic Protein Biomarkers for Liver Cirrhosis Based on Prospective Analysis of a Large-Scale Plasma Proteomics in the UK Biobank.

PURPOSE: Liver fibrosis and cirrhosis represent critical stages in the progression of chronic liver disease, yet their key molecular features remain i...

Artificial Intelligence in Xenotransplantation: A Prioritized Roadmap for Early Clinical Translation, Opportunities and Challenges.

Xenotransplantation represents a potential solution to the persistent global organ shortage, yet its clinical application remains stalled by complex i...

Noninvasive Classification of Advanced Liver Fibrosis Using Clinical Data and Non-Contrast MRI: Fusion of Clinical, Radiomic, and Deep Learning Models.

Noninvasive identification of advanced liver fibrosis (ALF), commonly defined as Scheuer stage S3 or higher, is important for the management of patien...

A data-driven approach to hepatitis C forecasting using machine learning and epidemiological models.

The hepatitis C virus is a significant global health concern and a major cause of chronic liver disease. Therefore, developing a mathematical model is...

Artificial intelligence in Latin American hepatology: current evidence, implementation barriers, and strategic priorities.

Chronic liver diseases are an increasing cause of morbidity and mortality in Latin America, driven by the convergence of alcohol and metabolic-associa...

Comparable Predictive Performance of Non-VCTE-Based Machine Learning Model for HBV-Infected Hepatocellular Carcinoma Risk.

BACKGROUND: Accurate risk stratification for hepatocellular carcinoma (HCC) among chronic hepatitis B (CHB) patients remains challenging. Vibration-co...

Integrated multi-omics and functional analyses reveal a GDCA-TGR5-mediated immunometabolic signature in anorexia nervosa.

BACKGROUND: Anorexia nervosa (AN) is frequently accompanied by metabolic disturbances and immune dysregulation, yet its peripheral molecular mechanism...

[Development and validation of an explainable machine learning-based model for predicting mortality risk in polytrauma patients].

Polytrauma is commonly defined as multisystem trauma involving at least two body regions with an Abbreviated Injury Scale (AIS) score ≥ 3, characteriz...

Development and internal validation of an interpretable machine learning model for predicting vancomycin-induced nephrotoxicity in hospitalized children.

INTRODUCTION: Vancomycin is widely used for severe Gram‑positive infections in children, but vancomycin‑induced nephrotoxicity (VIN) limits its safe a...

[Rational design and translational applications of hepatitis B virus-like particles].

Hepatitis B virus-like particles (HBV-VLPs), characterized by precise biomimetic topological architecture and favorable biocompatibility, have become ...

Ensuring pragmatic and equitable paths forward for hepatitis B virus infection eradication in Latin America.

INTRODUCTION: Latin America occupies a paradoxical position in hepatitis B virus (HBV) elimination: aggregate prevalence is low, yet the region remain...

Development and validation of a multidimensional machine learning model for predicting delayed graft function in deceased donor kidney transplantation.

PURPOSE: Delayed graft function (DGF) remains a significant complication following deceased donor kidney transplantation. This study aimed to develop ...

Integrative single-cell and machine-learning analysis identifies LGALS1 as a macrophage-associated diagnostic and prognostic biomarker in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is characterized by marked heterogeneity and an immunosuppressive microenvironment in which tumor-associate...