Inflammatory Bowel Disease

Disease and state dependent neural markers in adolescents with BD. Understanding the neural bases of mania, depression and remission in a data fusion approach.

BACKGROUND: Pediatric bipolar disorder (PBD) is a severe and disabling condition marked by alternating episodes of mania and depression, intermitted with periods of remission. A critical challenge in the field is to elucidate the neural mechanisms underlying these distinct mood states, as manic and depressive presentations reflect profoundly different clinical phenotypes. Despite their relevance, ...

Multi-modal sensing in colonoscopy: a data-driven approach.

Soft optical sensors hold potential for enhancing minimally invasive procedures like colonoscopy, yet their complex, multi-modal responses pose significant challenges. This work introduces a machine learning (ML) framework for real-time estimation of 3D shape and contact force in a soft robotic sleeve for colonoscopy. To overcome limitations of manual calibration and collect large datasets for ML,...

AI-Based Exhaled VOC Panels as Gut Microbiota-Derived Biomarkers for IBD Screening.

Inflammatory bowel diseases (IBD) present significant diagnostic and therapeutic challenges due to their heterogeneity. Here, we analyze exhaled volat...

Decipher the molecular network of PFOA in inflammatory bowel disease through integrating machine learning, molecular docking strategies, and validation in vitro.

OBJECTIVE: Perfluorooctanoic Acid (PFOA), widely recognized as an enduring environmental pollutant, is associated with immune system disruption and po...

Urinary steroid metabolome shows adrenal, gonadal, and neuroactive steroid dysregulation in adolescents with depressive symptoms.

BACKGROUND: Steroid hormone profiles in affective disorders suggest hypothalamic-pituitary-adrenal (HPA) axis dysregulation and may reveal novel thera...

AI-powered intestinal ultrasound in inflammatory bowel disease: Advancing toward automated disease assessment.

The management of inflammatory bowel disease (IBD) relies on accurate disease assessment and close monitoring to guide therapy and evaluate treatment ...

Meta-analysis of faecal microbiome studies followed by machine learning to identify intestinal disease-specific taxonomic signatures.

Alterations in the gut microbiome have been found to be associated with both inflammatory bowel disease (IBD) and irritable bowel syndrome (IBS), sugg...

Addressing Colonoscopy Burden Due to Artificial Intelligence Devices for Polyp Detection.

Skill degradation, false-positive burden, and translational gap of artificial intelligence-assisted colonoscopy.

Using machine learning to predict clinical remission with exclusive enteral nutrition in pediatric Crohn disease.

OBJECTIVES: Exclusive enteral nutrition (EEN) is a first-line treatment for induction of remission in luminal pediatric Crohn disease (pCD). However, ...

Clinical Efficacy of Real-Time Artificial Intelligence-Assisted Colonoscopy in Colorectal Polyp Detection: A Prospective Multicenter Randomized Controlled Trial.

BACKGROUND/AIMS: Early detection and removal of colon polyps are critical for preventing colorectal cancer. Computer-aided detection (CADe) systems ha...

Trajectories of affective disorders-the central structures of CRC/TRR 393.

The recurrent and often unpredictable course of affective disorders poses a critical challenge for long-term patient care. The CRC/TRR 393 consortium ...

Colonoscopy Quality and Strategies for Improvement.

Colonoscopy plays a pivotal role in colorectal cancer (CRC) screening and reduces CRC incidence and mortality. Its effectiveness depends on colonoscop...

Translating Gut Microbiota into Diagnostics: A Multidimensional Approach for the Diagnosis of Inflammatory Bowel Disease.

The gut microbiota has emerged as a key factor in the pathophysiology of inflammatory bowel disease (IBD), providing novel opportunities for diagnosti...

Resting-state functional connectivity of the fronto-limbic and default mode network as neural correlates of antidepressant response in major depressive disorder.

BACKGROUND: Major depressive disorder (MDD) is a leading cause of disability worldwide, yet antidepressant response remains highly variable, with many...

Microbiome based precision medicine through integrated multiomics and machine learning.

Gut microbiome (GME) is a dynamic ecosystem composed of diverse microorganisms with extensive functional potential that influence host physiology, end...

Spatially resolved airway niches: mapping epithelial-immune microenvironments in asthma.

INTRODUCTION: Spatially resolved omics has reconceptualized the bronchial wall as a mosaic of epithelial - immune microenvironments whose local molecu...

Interpretable machine learning models for predicting depression status and remission three years later in older adults in China: A longitudinal study.

BACKGROUND: Depression significantly impacts older adults, making it valuable to use machine learning to predict their future depressive status and as...

Improving Colorectal Cancer Screening and Risk Assessment through Predictive Modeling on Medical Images and Records.

Colonoscopy screening effectively identifies and removes polyps before they progress to colorectal cancer (CRC), but current follow-up guidelines rely...

A prospective study evaluating an artificial intelligence-based system for withdrawal time measurement.

Withdrawal time has emerged as a critical quality measure in colonoscopy for colorectal cancer screening. Owing to the high variability in calculating...