Gastroenterology

Semi-Automatic Assessment of Crohn's Disease Activity by Combined Analysis of Bowel Lesions and Creeping Fat.

PURPOSE: To develop and evaluate Crohn-BOOST, an open-source tool enabling semi-automatic segmentati...

Combining AI to reveal CCDC3-mediated pathways of colorectal cancer liver metastasis.

In colorectal cancer liver metastases, chromosomal instability (CIN) serves as a critical hallmark l...

Overcoming gastrointestinal mucosal barriers: Mechanistic innovations and technical advances in mucosal targeting strategies for animal oral vaccines.

Infectious diseases caused by pathogenic microorganisms (such as Escherichia coli, Avian influenza v...

Artificial intelligence assistance improves endoscopist accuracy for gastric cancer dysplasia and intestinal metaplasia.

Prediction of Massage Force and Intra-abdominal Wall Deformation During Massage by a Digital Twin Model Based on an Abdominal Finite Element Model.

PURPOSE: Constipation is a prevalent disorder of the digestive system, and abdominal massage is comm...

Predicting VRE Infection After Liver Transplantation With a Time-Updated Colonization Score.

BACKGROUND: Vancomycin-resistant Enterococcus (VRE) infection is a life-threatening complication aft...

Utility of augmented reality in endoscopic surgery for stones: European Association of Urology endourology up-to-date review.

PURPOSE OF REVIEW: The development of digital solutions has a direct impact on the modern understand...

BCLC classification and AI-based image quantification: What is meant to be will come together - but how and when?: BCLC and AI-based image quantification.

The Barcelona Clinic Liver Cancer (BCLC) classification has been the mainstay for prognostic assessm...

A noninvasive model for predicting intrahepatic venovenous shunts before HVPG measurement: a multiple cohort study.

OBJECTIVES: This study aimed to construct a machine learning (ML) model to facilitate non-invasive i...

Machine-learning with multiomics for radiotherapy-induced acute rectal toxicities and survival outcome in patients with cervical cancer.

Automatic Hepatic Steatosis Quantification using Low-Dose CT with deep learning-based noise reduction and CT Fat Fraction Analysis Software.

OBJECTIVES: To evaluate the accuracy of CT-derived fat fraction (CDFF) software for quantifying hepa...

Impact of Deep Learning-Based Time-of-Flight PET Images of Small Tumors Using a Human Anatomic Phantom.

Time-of-flight (ToF) in PET improves image quality by enhancing the signal-to-noise ratio, and recen...

Deep learning linking mechanistic models to single-cell transcriptomics data reveals transcriptional bursting in response to DNA damage.

Cells must adopt flexible regulatory strategies to make decisions regarding their fate, including di...

Cell-free DNA fragmentomes for noninvasive detection of liver cirrhosis and other diseases.

Accessible liquid biopsies, including analyses of genome-wide cell-free DNA (cfDNA) fragmentation, a...

Cell-free chromatin state tracing reveals disease origin and therapy responses.

Cell-free DNA in blood originates from fragmented chromatin released by dying cells from both health...

Technology-enabled insights into SLC transporters in MAFLD: redefining the multi-hit pathogenesis and therapeutic landscape.

Recent advances in structural biology, functional genomics, and artificial intelligence (AI) have ex...

Integrating machine learning of bulk and single cell RNA data to characterize immune mechanism of m6A related mitophagy genes in malignant gastric cancer.

BACKGROUND AND OBJECTIVE: Gastric cancer is a heterogeneous and complicated epithelial cancers. Chro...

Functional traits shape gut microbial assembly beyond phylogeny in estuarine fish.

Host-specific patterns of symbiotic microbiomes are ubiquitous in nature, yet the intricate interpla...

Overcoming missing data in spatial metabolomics with machine learning imputation to accelerate downstream discovery.

Mass spectrometry imaging (MSI)-based spatial metabolomics exhibits extensive missing values; yet, p...

Development and validation of a multimodal deep learning model for early esophageal squamous neoplasia detection and invasion depth prediction.

Early detection of esophageal squamous cell carcinoma (ESCC) is critical for optimizing patient outc...

Natural language processing of biomedical text to map and prioritize protein-disease associations in HFpEF.

The validation of promising clinical biomarkers, molecular mechanisms, and novel drug targets in car...