Gastroenterology

Development and Validation of a Machine Learning Model for Predicting 30-Day Mortality and Early Endoscopic Hemostatic Intervention in Acute Upper Gastrointestinal Bleeding.

OBJECTIVE: Accurate pre-endoscopic risk stratification is essential in acute upper gastrointestinal bleeding (UGIB). Established scores predict mortality but have limited ability to identify patients requiring early therapeutic endoscopy. We developed and temporally validated a pre-endoscopic machine learning model to predict 30-day mortality and early (≤24 h) endoscopic hemostatic intervention an...

Risk Factor Analysis and Nomogram for Predicting 28-day in-hospital Mortality in ICU Patients with Liver Necrosis.

INTRODUCTION: The mortality risk factors in intensive care unit (ICU) patients with liver necrosis (LN) remain unclear. This study aimed to develop a prediction model for mortality risk in LN patients to assist clinical practice. METHODS: We enrolled 1153 acute and subacute LN patients from the MIMIC-III database, randomly divided into training and validation cohorts. LASSO regression was used to ...

Performance of the Techcyte AI-based image analysis system for coproparasitological diagnosis in clinical stool specimens: a retrospective evaluation study.

UNLABELLED: Coproparasitological stool analysis based on microscopic examination is the reference diagnostic technique routinely performed in clinical...

A deep learning framework for quantification of hepatic steatosis in whole-slide images by tile-level scoring and screening.

Objective.To develop a deep learning framework for the efficient and accurate quantification of hepatic steatosis in whole-slide images (WSIs).Approac...

Machine Learning-Based Models to Predict Drug-Induced Liver Injury (DILI) to Assist Medicinal Chemistry.

Drug-induced liver injury (DILI) is a leading cause of drug failure and post-market withdrawals. Traditional preclinical methods fail to detect up to ...

Identification of circadian rhythm-associated key genes in metabolic dysfunction-associated fatty liver disease.

As of now, current studies have confirmed that circadian rhythm genes (CRGs) can modulate the onset and development of metabolic dysfunction-associate...

High-Throughput Olink Proteomics Elucidates the Immuno-Neurological Landscape of Gastric Cancer.

Gastric cancer (GC) ranks as the third leading cause of cancer-related mortality globally. A comprehensive and precise proteomic study of GC tissues c...

Efficacy and Hepatotoxicity of Psoralea corylifolia L.: A Meta-Analysis and Machine Learning Assessment in Postmenopausal Osteoporosis.

ETHNOPHARMACOLOGICAL RELEVANCE: Psoralea corylifolia L. (P. corylifolia, also known as Cullen corylifolium (L.) Medik.) is a traditional medicinal her...

EGID: A Comprehensive Multi-label Endoscopic Image Dataset for Gastritis Classification.

Chronic atrophic gastritis is a well-recognized precancerous condition, emphasizing the need for accurate endoscopic classification. However, existing...

Predictors of same-day discharge following bariatric surgery using machine learning.

BACKGROUND: Same-day discharge (SDD) following bariatric surgery is becoming increasingly more common to reduce healthcare utilization. However, predi...

Automated Assessment of Surgical Quality in Distal Gastrectomy: Development of a Novel Computer Vision Model Based on the Critical View of Quality (CVQ).

OBJECTIVE: To evaluate the clinical validity of the critical view of quality (CVQ) as a measure of lymphadenectomy quality in minimally invasive dista...

Machine Learning Models for Prediction of Response to Therapeutic Plasma Exchange in Pediatric Acute Liver Failure.

BACKGROUND: Therapeutic plasma exchange (TPE) artificially lowers prognostic markers such as INR and bilirubin, complicating timely decisions regardin...

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study.

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage increases risk of vascular events...

Path beyond the blind end-unravel the imaging spectrum of appendiceal pathologies.

The appendix is involved in a diverse spectrum of inflammatory, infectious, benign, and malignant conditions that extend far beyond acute appendicitis...

Quantitative Assessment of Nanoplastic Toxicity Risks Across Aquatic Trophic Levels with Data-Driven Models and Exposure Experiments.

Emerging contaminants such as nanoplastics (NPs) pose significant risks to aquatic ecosystems. However, the key features governing NPs toxicity and th...

A HRH1-YAP1 feedback loop drives pancreatic cancer progression and predicts therapeutic response.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy with a dismal prognosis, characterized by an immunosuppressive tumor microenviro...

2-Hydroxyisobutyrylation and Phosphorylation Crosstalk Guides Metastasis Prediction and Immunotherapy in Esophageal Squamous Cell Carcinoma.

Posttranslational modification (PTM) is pivotal in cancer progression. However, the mechanisms, biological function, and clinical significance underly...

Hepatology e-consult responses generated by artificial intelligence demonstrate accuracy but require human oversight.

BACKGROUND: Electronic consultations (e-consults) improve specialist access but burden providers. We developed LiVersa, a customized large language mo...

Integrating 2.5D multi-modal CT imaging with serum triglycerides for early risk stratification in hypertriglyceridemia-induced acute pancreatitis: A multicenter study.

OBJECTIVES: To develop and externally validate a clinical-radiological framework that fuses 2.5D deep learning features from dual-phase computed tomog...

Development and validation of the SYSU-score for MRI-based transmural healing assessment in Crohn's disease: a dual-center study.

OBJECTIVES: Standardizing magnetic resonance enterography (MRE)-defined transmural healing (TH) remains challenging in Crohn's disease (CD) despite it...