Gastroenterology

Explainable artificial intelligence for prediction of refractory ulcerative colitis: analysis of a Japanese Nationwide Registry.

OBJECTIVE: Ulcerative colitis (UC) is a chronic inflammatory bowel disease for which remission is dependent on corticosteroid (CS) treatment. The diversity of disease pathophysiology necessitates optimal case-specific treatment selection. This study aimed to identify prognostic factors for refractory UC using a machine learning model based on nationwide registry data.

Antioxidant bioactivity of sunflower protein hydrolysates in Caco-2 cells and in silico structural properties.

Sunflower protein hydrolysate (SPH), with 95 % reduced phenolic content, was studied for its protective effects against oxidative stress in intestinal cells (Caco-2). Produced via alcalase hydrolysis, SPH's molecular weight, amino acid composition, and hydrophobicity were characterized. The antioxidant activity of SPH, tested by ABTS, was maintained in Caco-2 cells under oxidative stress, modulati...

SurvGraph: A hybrid-graph attention network for survival prediction using whole slide pathological images in gastric cancer.

Whole slide pathological images have shown significant potential for patient prognostication. Graph representation learning provides a robust framewor...

Predicting in vitro assays related to liver function using probabilistic machine learning.

While machine learning has gained traction in toxicological assessments, the limited data availability requires the quantification of uncertainty of i...

Nutritional and lifestyle predictors of rectal bleeding in functional constipation: A machine learning approach.

BACKGROUND: Rectal bleeding among young adults is an increasingly common clinical concern often linked with chronic constipation and unhealthy lifesty...

Improving image quality and diagnostic performance using deep learning image reconstruction in 100-kVp CT enterography for patients with wide-range body mass index.

OBJECTIVE: To assess the clinical value of the deep learning image reconstruction (DLIR) algorithm compared with conventional adaptive statistical ite...

Comparison of clinical, radiomics, deep learning, and fusion models for predicting early recurrence in locally advanced rectal cancer based on multiparametric MRI: a multicenter study.

OBJECTIVE: Predicting early recurrence (ER) in locally advanced rectal cancer (LARC) is critical for clinical decision-making. This study aimed at com...

Deep-learning based automated pancreas segmentation on CT scans of chronic pancreatitis patients.

OBJECTIVES: This study aimed to develop an artificial intelligence (AI)-based segmentation model for accurate delineation of the complex pancreas in p...

Screening and preliminary analysis of antimicrobial peptide genes in Octopussinensis.

Antimicrobial peptides (AMPs) are small molecular peptides that widely exist in organisms to resist external microbial invasion and play a crucial rol...

Effect of Static vs. Conversational AI-Generated Messages on Colorectal Cancer Screening Intent: a Randomized Controlled Trial

Large language model (LLM) chatbots show increasing promise in persuasive communication. Yet their real-world utility remains uncertain, particularl...

CL-Polyp: A Contrastive Learning-Enhanced Network for Accurate Polyp Segmentation

Accurate segmentation of polyps from colonoscopy images is crucial for the early diagnosis and treatment of colorectal cancer. Most existing deep le...

ADPv2: A Hierarchical Histological Tissue Type-Annotated Dataset for Potential Biomarker Discovery of Colorectal Disease

Computational pathology (CoPath) leverages histopathology images to enhance diagnostic precision and reproducibility in clinical pathology. However,...

Serum-Based Detection of Pancreatic and Ovarian Cancer via a Nanoparticle-Enhanced Fluorescence Array and Machine Learning.

: Early detection of oncological diseases such as pancreatic ductal adenocarcinoma (PDAC) and ovarian cancer (OV) is pivotal for successful treatment ...

Label-free single-cell phenotyping to determine tumor cell heterogeneity in pancreatic cancer in real time.

Resistance to chemotherapy of pancreatic ductal adenocarcinoma (PDAC) is largely driven by intratumoral heterogeneity (ITH) due to tumor cell plastici...

Integrating Inertial Microfluidics with SERS Bioprobe for Efficient Enrichment and Accurate Identification of Tumor Cells in Gastric Fluid and Ascites.

Gastric cancer (GC) is a disease with high mortality rates and remains a central focus in medical research. Efficient enrichment, separation, and prec...

Self-supervised Deep Learning for Denoising in Ultrasound Microvascular Imaging

Ultrasound microvascular imaging (UMI) is often hindered by low signal-to-noise ratio (SNR), especially in contrast-free or deep tissue scenarios, w...

Protocol for a multicenter randomized controlled trial to assess the usefulness of computer-aided detection systems for colonoscopy in colorectal cancer screening in the Asia-Pacific region (project CAD/NCCH2217).

Ensuring the high quality of colonoscopies in colorectal cancer (CRC) screening is essential to reducing CRC. Recently, computer-aided detection syste...

Evaluation of the role of comedication properties in the severity of drug-induced liver injury using machine learning techniques.

BACKGROUND: Drug-induced liver injury (DILI) is a complex liver pathology modulated by multiple factors, most of which remain unknown. Previous studie...

PLUS: Plug-and-Play Enhanced Liver Lesion Diagnosis Model on Non-Contrast CT Scans

Focal liver lesions (FLL) are common clinical findings during physical examination. Early diagnosis and intervention of liver malignancies are cruci...

CPKD: Clinical Prior Knowledge-Constrained Diffusion Models for Surgical Phase Recognition in Endoscopic Submucosal Dissection

Gastrointestinal malignancies constitute a leading cause of cancer-related mortality worldwide, with advanced-stage prognosis remaining particularly...