Gastroenterology

ACAT1-mediated lactylation reprogramming governs immune-stromal crosstalk in ulcerative colitis.

Ulcerative colitis (UC), a chronic inflammatory bowel disorder characterized by progressive colonic inflammation, presents escalating global incidence rates and heightened risk of colorectal carcinogenesis. Despite emerging evidence implicating lactylation - a novel post-translational modification - in diverse biological pathways, its mechanistic involvement in UC pathogenesis remains poorly eluci...

Machine learning-based clustering differentiates bilateral hepatocellular carcinoma characteristics and prognosis.

BACKGROUND: Bilateral hepatocellular carcinoma represents a biologically heterogeneous disease with uncertain optimal surgical selection criteria. Although hepatic resection can provide survival benefit in selected patients, outcomes remain variable, and phenotypic determinants of prognosis have not been clearly defined. METHODS: Patients who underwent curative-intent hepatectomy for bilateral hep...

Multiparametric MRI-Based Integrated Analysis of Clinical, Radiomics, Deep Learning, and Machine Learning for Predicting Tumor Proliferation and Prognosis in Locally Advanced Rectal Cancer.

RATIONALE AND OBJECTIVES: This study aimed to develop and validate a predictive model integrating clinical, radiomics, deep learning (DL), and machine...

Digital SERS Nanoprobe Immunoassay With Single-Particle Sensing Resolution for Detection of Pancreatic Cancer Biomarkers From Clinical Blood Samples.

Surface-enhanced Raman scattering (SERS) nanoprobe-based immunoassay is an emerging liquid biopsy modality for the detection of blood biomarkers. Howe...

Machine learning nomograms for gastric cancer: addressing data limitations in SEER-based models.

Machine Learning in Predicting the Risk of Esophagogastric Variceal Bleeding Among Patients With Liver Cirrhosis: Systematic Review and Meta-Analysis.

BACKGROUND: Liver cirrhosis (LC) can lead to several complications. Esophageal variceal bleeding (EVB) and esophagogastric variceal bleeding (EGVB) ar...

Impact of an AI prognostic tool on clinician performance in colorectal liver metastases.

While thousands of AI prediction models are published annually, few are adopted into routine practice, partly because improved statistical performance...

Endo-Hepatology and Artificial Intelligence: New Avenues for Diagnosis and Intervention.

Artificial intelligence (AI) is gaining momentum in the field of endo-hepatology, offering potential improvements in diagnosis, risk stratification, a...

Deep learning-enabled scaffolding of spatial arrays of PfCSP epitopes.

Malaria is a leading cause of disease in developing countries. The licensed malaria vaccine RTS,S/AS01 confers partial protection in part due to the e...

irAE-GPT: leveraging large language models to identify immune-related adverse events in electronic health records and clinical trial datasets.

BACKGROUND: Large language models (LLMs) have emerged as transformative technologies, revolutionising natural language understanding and generation ac...

Magnetically controlled capsule endoscopy: Innovations, standardized practice, and emerging clinical roles.

Capsule endoscopy has transformed small bowel evaluation but remains limited for gastric examination because of passive, peristalsis dependent movemen...

Automatic Recognition and Prognostic Prediction of Colorectal Liver Metastases Using a Multi-Scale Deep Learning Framework: Model Development and Validation Study.

BACKGROUND: Colorectal cancer liver metastasis (CRLM) presents considerable challenges in both diagnosis and prognosis, as conventional approaches oft...

Development and external validation of a machine learning model for predicting chronic critical illness in ICU patients with acute pancreatitis.

BACKGROUND: To develop and validate a machine learning (ML) model to assess the risk of chronic critical illness (CCI) in intensive care unit (ICU) pa...

Imaging-based stratification of Claudin 18.2-positive gastric adenocarcinoma using 18F-FDG PET/CT radiomics.

PURPOSE: This study aimed to develop and validate a non-invasive, multimodal radiomics model based on preoperative 1⁸F-FDG PET/CT to predict CLDN18.2 ...

Screening and dynamic change study of microbial and metabolite markers for calf diarrhea based on multi-omics and machine learning.

UNLABELLED: Neonatal calf diarrhea is a leading cause of calf mortality and substantial economic loss in the livestock industry, yet the dynamic micro...

Deep learning reconstruction for 40-keV virtual monoenergetic CT of colon cancer: evaluation of image quality and edge sharpness.

BACKGROUND: Virtual monoenergetic imaging (VMI) at 40 keV improves iodine attenuation in colon cancer CT but is constrained by severe image noise. Dee...

HCCaging: a liver physiological aging-related biomarker for hepatocellular carcinoma diagnosis based on transcriptome data.

Aging is a fundamental biological process that influences cancer development in a context-dependent manner; however, how aging-related programs manife...

A fully automated CT-based pelvimetry pipeline for quantifying mid-pelvic surgical workspace in rectal cancer.

PURPOSE: Pelvimetry may aid preoperative planning in rectal cancer surgery, yet manual measurements are time-consuming and MRI-based methods require d...

High-resolution LA-ICP-MS imaging combined with attention-enhanced residual network reveal cadmium-induced metal distribution heterogeneity and toxicity in Mytilus galloprovincialis.

Marine bivalves often face heavy metal stress, yet we still lack of high-resolution way to observe the metal pollution status in soft tissue. This stu...

Temporal AI-assisted compressed sensing for high-resolution, motion-robust small-bowel MR enterography without antiperistaltic agents: a feasibility study.

OBJECTIVES: To evaluate whether temporal AI-assisted compressed sensing (tACS) enables high-resolution, motion-robust magnetic resonance enterography ...