Gastroenterology

Universal gene-level bimodality in natural microbial communities.

Bimodality-the coexistence of two peaks in trait distributions-is common in natural ecosystems. In microbiomes, bimodality of species abundances is known. However, whether this pattern applies to community functionality remains unclear. Here, we systematically investigate the abundance distributions of individual genes in different microbiomes, from human gut to ocean, revealing widespread gene-le...

Letter Regarding "Artificial Intelligence Model for Automated Identification of Bowel Preparation for Colonoscopy (AI-PREPOO): A Multicenter Study".

Hepatic and abdominal adiposity in type 2 diabetes as assessed with machine learning on computed tomography scans.

AIMS: The combined assessment of multiple abdominal imaging traits in relation to type 2 diabetes remains incompletely characterised. The study examin...

Artificial intelligence enhances screening efficiency for inflammatory bowel disease clinical trials: a prospective study.

An LLM-based AI tool significantly improved identification of potentially eligible patients and screening efficiency for IBD clinical trials, outperfo...

Deep Learning-Based Auto-Navigation for Free-Breathing Golden-Angle Radial MRI.

PURPOSE: To develop a deep learning-based auto-navigation technique for free-breathing golden-angle radial MRI named RANGR (Respiratory Auto-Navigator...

Gut Microbiome as a Lifestyle Risk Factor Associated with Prostate Cancer.

BACKGROUND AND OBJECTIVE: Most prostate cancer prevention strategies suggest lifestyle modifications, which lack personalization. Gut microbiome is in...

Analysing DCE-MRI scans using hybrid techniques for early detection of prostate cancer based on fusion features of handcrafted and deep learning features.

Prostate cancer is among the most diagnosed malignancies in men worldwide and a leading cause of cancer-related mortality. Early and accurate diagnosi...

R-GAT: cancer document classification leveraging graph-based residual network for scenarios with limited data.

Accurate classification of cancer-related biomedical abstracts is critical for advancing cancer informatics and supporting decision-making in healthca...

Machine learning-based cfDNA fragmentation profiling using automated capillary electrophoresis for early detection of hepatocellular carcinoma.

BACKGROUND: Early detection of hepatocellular carcinoma (HCC) remains a significant clinical challenge due to the limited sensitivity of current surve...

Identification and Validation of Liver Transplantation-Induced Acute Lung Injury Biomarkers Using a Bioinformatics and Experimental Approach.

BACKGROUND Acute lung injury (ALI) after liver transplantation (LT) is a critical complication negatively affecting transplant outcomes and patient su...

Nuclear medicine in predicting hepatocellular carcinoma response.

Immune checkpoint inhibitors and anti-angiogenic targeted therapies have improved outcomes in hepatocellular carcinoma (HCC), but responses remain het...

AI-Enhanced Vibrational Capsule for Minimally Invasive Detection of Abnormal Bowel Tissue.

Colorectal cancer remains one of the leading causes of cancer mortality, and its prognosis is strongly dependent on early detection. Conventional diag...

Multi-encoder U-Net benchmarking for LiTS17 Liver-Tumor segmentation: accuracy-efficiency trade-offs across training durations.

OBJECTIVES: Accurate liver and tumor segmentation from CT is fundamental for diagnosis, treatment planning, and longitudinal monitoring of liver cance...

Machine learning models classifiers enable a strong prediction of radioembolization-induced liver disease, and define a new bilirubin threshold for selection of patients.

PURPOSE: Selective Internal Radiotherapy (SIRT) is an established treatment option for hepatocellular carcinoma (HCC). However, a major complication i...

Integration of in vitro and in silico approaches enables prediction of drug-induced liver injury.

Drug-induced liver injury (DILI) is a major cause of drug attrition and poses a significant threat to patient safety. However, current preclinical pre...

Radiomics for early detection of pancreatic cancer: a systematic review and meta-analysis.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is one of the lethal malignancies, in which accurate and faster detection is required in high-risk...

Harnessing artificial intelligence in gastrointestinal endoscopy for early detection of dysplastic lesions in inflammatory bowel disease.

Artificial intelligence (AI) has become an increasingly valuable tool in gastrointestinal endoscopy, especially in the context of inflammatory bowel d...

Artificial intelligence-assisted middle meningeal artery embolization for chronic subdural hematoma with overlay visualization.

The effectiveness of middle meningeal artery (MMA) embolization for chronic subdural hematoma is well established,1-3 and distal and multibranch penet...

Epidemiological Trajectories and Quality of Care Disparities of MASLD in Asia, 1990-2023.

BACKGROUND: To characterize temporal and geographic patterns of metabolic dysfunction-associated steatotic liver disease (MASLD) across Asia from 1990...

Machine learning-predicted insulin resistance is a risk factor for 12 types of cancer.

Insulin resistance is suggested to be a risk factor for cancer; however, large-scale epidemiological evidence linking insulin resistance to cancer rem...