Inflammatory Bowel Disease

Application of artificial intelligence in colonoscopy imaging for polyp analysis-A systematic review.

The colon is a major component of the digestive system, so early detection of colorectal polyps is essential in preventing colorectal cancer, which is a leading cause of cancer-related death worldwide. While colonoscopy remains the gold standard for polyp detection, its diagnostic accuracy is highly operator-dependent. Recent advances in Deep Learning (DL), a branch of Artificial Intelligence (AI)...

Mechanistic evidence for dibutyl phthalate as an environmental trigger for inflammatory bowel disease.

Dibutyl phthalate (DBP) is a ubiquitous pollutant, but its molecular link to inflammatory bowel disease (IBD) is undefined. We employed an integrative network toxicology framework, combining DBP target databases with IBD patient transcriptomics to address this gap. A computational pipeline using machine learning and molecular docking predicted a core six-gene signature (KYNU, PCK1, LCN2, CDC25B, E...

Plasma metabolomics identifies lipid mediators linking depression and cognitive decline in late-life depression.

BACKGROUND: Late-life depression (LLD) features recurrent episodes and frequently co-exists with cognitive impairment, which predicts worse outcomes a...

Advances in the Application of Digital Health Technologies in the Management of Patients With Inflammatory Bowel Disease.

Inflammatory bowel disease (IBD) is a chronic disorder that requires long-term follow-up and individualized management. With the rapid development of ...

Characterizing endotypes in chronic rhinosinusitis: emerging research and clinical applications.

PURPOSE OF REVIEW: The purpose of this study is to describe why this review is timely and relevant. Endotyping, the organization of rhinologic inflamm...

Deep learning based treatment remission prediction to transcranial direct current stimulation in bipolar depression using EEG power spectral density.

Bipolar disorder is characterized by marked changes in mood and activity levels and is a leading cause of disability worldwide. We sought to investiga...

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 w...

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 signif...

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...