Latest AI and machine learning research in gastroenterology for healthcare professionals.
Plasma metabolomics offers significant potential for non-invasive biomarker discovery in gastric cancer (GC), yet conventional analytical workflows face challenges in absolute quantification and biological interpretability, hindering clinical translation. Here we present an innovative multi-phase hybrid framework integrating untargeted metabolomics with relative- and absolute-quantitative targeted...
BACKGROUND: Given the interplay of cirrhosis with malignancy, management of hepatocellular carcinoma (HCC) relies on multidisciplinary clinician judgement to guide treatment. Accurate survival prediction would facilitate decision-making and resource allocation while maintaining patient-centred care with optimized survival outcomes while avoiding futility, particularly regarding liver transplant. M...
BACKGROUND: Characterizing the tumor immune microenvironment (TIME) is essential for understanding anti-tumoral responses in colon cancer. This study ...
BACKGROUND: The gut microbiota adapts to and shapes the host's metabolic state through affecting circulating metabolites and consequent gene regulator...
BACKGROUND: Minimally invasive colorectal surgery is characterized by significant procedural variability, a difficult learning curve, and complication...
This study presents a novel integrative approach for the analysis of high-dimensional gene expression data, leveraging the complementary strengths of ...
BACKGROUND: Non-invasive biomarkers with biological rationale are needed for identifying patients with progressive metabolic dysfunction-associated st...
Postoperative recurrence (POR) is a major challenge in the long-term management of Crohn's disease (CD), affecting up to 70% of patients within the fi...
BACKGROUND: Accurate risk stratification of biliary complications (BCs) after liver transplantation (LT) remains challenging. This study aimed to deve...
Objective.To develop deep-learning (DL) predictive models of internal gastrointestinal (GI) gas from radiographs, a surrogate for dose degradation in ...
Increased sensory nerve density has been described in type II inflammatory conditions and is linked to eosinophil and mast cell infiltration and neuro...
Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal forms of cancer, with a five-year survival rate below 10% primarily due to late...
Rare tumor diseases are difficult to diagnose and there is a lack of routine diagnostic procedures. Approaches must be found that allow comprehensive ...
BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is a major cause of cancer-related mortality worldwide, with a high prevalence and poor prognosi...
BACKGROUND: Testing for Blood-Borne-Viruses (BBVs) such as the human immunodeficiency virus (HIV), hepatitis C virus (HCV) and hepatitis B virus (HBV)...
BACKGROUND: Machine-learning models based on tissue transcriptomic data are powerful tools for disease classification. However, their clinical adoptio...
Metabolic dysfunction-associated fatty liver disease (MASLD) is a highly prevalent liver condition with a complex etiology increasingly linked to air ...
Clinical translation of novel therapies can be hindered by heterogeneity-driven sample size inflation in late-stage trials. In acetaminophen-induced l...
OBJECTIVE: Magnetic resonance imaging (MRI) and computed tomography (CT) are commonly used to measure organ volumes, but accuracy has not been methodi...
Diabetic colitis is a severe gastrointestinal complication of type 2 diabetes, which presents the key pathophysiological hallmarks of hyperglycemia, i...