Gastroenterology

Biomimetic Electrochemical Chip Integrated with Closed-Loop AI for Dynamic Dopamine Decoding and Neuromodulation.

Bioelectronic systems integrated with artificial intelligence (AI) are transforming neurochemical diagnostics, enabling intelligent, real-time decoding of brain chemistry. Here, we present an AI-driven biomimetic electrochemical chip with intestine-inspired wrinkled MoS2 electrodes, enabling dynamic in vivo dopamine monitoring and neuromodulation. This wrinkled structural design promotes efficient...

The regional landscape of the human colon culturome in health and cystic fibrosis.

UNLABELLED: Cystic fibrosis (CF) alters gut physiology, yet its impact on microbial communities across colonic regions (ascending, transverse, descending colon) and microhabitats (lumen, mucosa) remains incompletely understood. Here, we applied culturomics to characterize gut microbiota in a small cohort of 32 individuals (22 non-CF, 10 CF). Persons with CF (pwCF) exhibited significantly higher vi...

Comparative urinary metabolomics reveals unique and shared pathways in COVID-19 and liver diseases.

INTRODUCTION: The COVID-19 pandemic and liver diseases both cause significant metabolic disturbances, yet the specific mechanisms driving these change...

Evaluating the cost-effectiveness of artificial intelligence in Barrett's surveillance.

Artificial intelligence (AI) has emerged as a promising tool to detect early dysplasia in Barrett's esophagus (BE). However, the cost-effectiveness of...

Machine learning framework for early identification of high-spending Crohn's disease patients using administrative claims.

OBJECTIVES: To develop and evaluate a machine learning (ML) model that predicts Crohn's disease (CD) patients responsible for the top quartile of heal...

Delta radiomics-based nomogram for preoperative prediction vessels encapsulating tumor clusters (VETC) and prognosis in hepatocellular carcinoma using dynamic contrast-enhanced CT.

BACKGROUND: Vessels encapsulating tumor clusters (VETC) serve as a crucial adverse prognostic indicator in hepatocellular carcinoma (HCC). This study ...

From scalpel to robot: evolution and outlook of oncologic robotic surgery in Colombia.

INTRODUCTION: Robotic surgery has transformed the management of oncologic pathologies by offering minimally invasive approaches with improved precisio...

Identifying Subgroups of People Living With HIV in British Columbia, Canada Based on Sexually Transmitted and Blood-Borne Infection Testing and Diagnostic Laboratory Data: A Retrospective Cohort Study.

BACKGROUND AND AIMS: Although combination antiretroviral therapy has decreased morbidity and mortality in people living with HIV (PLWH), the prevalenc...

Computer-Aided Detection-Assisted Colonoscopy Teaches Gaze to Improve Adenoma Detection in First-Year Gastroenterology Fellows.

BACKGROUND AND AIMS: The impact of computer-aided detection (CADe)-assisted colonoscopy on gastroenterology fellow trainees remains incompletely defin...

msCNN-PLM-FAD: Enhanced predicting FAD binding sites by using protein language representation combined with multiple separable windows convolutional neural networks.

The FAD binding sites classification problem is crucial because it is directly related to many diseases, such as flavoprotein-associated diseases, dev...

From permeability to prediction: evolving strategies for evaluating oral drug absorption.

Oral drug administration, preferred for patient compliance and convenience, encounters significant bioavailability challenges arising from complex phy...

Signature-aware deep learning reveals distinct driver gene programs and mutational processes in glioblastoma and colon adenocarcinoma.

The precise identification of cancer driver mutations is essential for precision oncology; however, it remains a significant challenge because of the ...

LCMS-Net: Deep Learning for Raw High Resolution Mass Spectrometry Data Applied to Forensic Cause-of-Death Screening.

Current preprocessing workflows for untargeted metabolomics using liquid chromatography-high resolution mass spectrometry (LC-HRMS) are time-consuming...

Towards deep-learning based detection and quantification of intestinal metaplasia on digitized gastric biopsies: a multi-expert comparative study.

Current gastric cancer (GCa) risk systems are prone to errors since they evaluate a visual estimation of intestinal metaplasia percentages in histopat...

From manual parametric to artificial intelligence-based automation: A systematic review of recent advances in endoscopic surgical skills evaluation.

Evaluating surgical skills is critical to surgical training. Numerous methods and scoring scales have recently emerged to assess skills. This study sy...

Evaluating deep learning models for pancreatic cancer diagnosis.

Pancreatic cancer is a highly aggressive and often fatal disease, with early detection being a key factor for improving patient survival. Recent advan...

Research progress of machine learning applications in gastric cancer diagnosis and therapy.

Gastric cancer (GC), a malignant neoplasm originating from the gastric mucosal epithelium, represents one of the most prevalent cancers worldwide. Ear...

Ensemble model assisted classification of gastrointestinal bleeding using wireless capsule endoscopy.

Wireless Capsule Endoscopy (WCE) is a useful method for imaging the intestines painlessly and looking into gastrointestinal tract diseases. The invest...

Identification of Gene Signatures Differentiating Cancer from Normal Tissues Across Histological Classifications of Gastric Adenocarcinoma via Machine Learning Methods.

Gastric adenocarcinoma is a significant global health concern. Among the myriad histologic classification methods for this cancer, the Lauren classifi...

Diagnosis of Gastric Intestinal Metaplasia: Histology, Endoscopy, and Artificial Intelligence.

Background Gastric intestinal metaplasia (GIM) is a well-established precancerous lesion and key biomarker for assessing the risk of gastric cancer. H...