Inflammatory Bowel Disease

Cost-effectiveness of artificial intelligence for screening colonoscopy: a modelling study.

BACKGROUND: Artificial intelligence (AI) tools increase detection of precancerous polyps during colonoscopy and might contribute to long-term colorectal cancer prevention. The aim of the study was to investigate the incremental effect of the implementation of AI detection tools in screening colonoscopy on colorectal cancer incidence and mortality, and the cost-effectiveness of such tools.

Real-Time Artificial Intelligence-Based Optical Diagnosis of Neoplastic Polyps during Colonoscopy.

BACKGROUND: Artificial intelligence using computer-aided diagnosis (CADx) in real time with images acquired during colonoscopy may help colonoscopists distinguish between neoplastic polyps requiring removal and nonneoplastic polyps not requiring removal. In this study, we tested whether CADx analyzed images helped in this decision-making process. METHODS: We performed a multicenter clinical study ...

Deep learning of chest X-rays can predict mechanical ventilation outcome in ICU-admitted COVID-19 patients.

The COVID-19 pandemic repeatedly overwhelms healthcare systems capacity and forced the development and implementation of triage guidelines in ICU for ...

Weakly supervised end-to-end artificial intelligence in gastrointestinal endoscopy.

Artificial intelligence (AI) is widely used to analyze gastrointestinal (GI) endoscopy image data. AI has led to several clinically approved algorithm...

The Role of Gabapentinoids in the Substance Use Pattern of Adult Germans Seeking Inpatient Detoxification Treatment - A Pilot Study.

To shed more light on the addictive power of the gabapentinoids (GPTs) gabapentin and pregabalin, we performed a structured face-to-face interview wit...

Graph-Based Region and Boundary Aggregation for Biomedical Image Segmentation.

Segmentation is a fundamental task in biomedical image analysis. Unlike the existing region-based dense pixel classification methods or boundary-based...

Combining explainable machine learning, demographic and multi-omic data to inform precision medicine strategies for inflammatory bowel disease.

Inflammatory bowel diseases (IBDs), including ulcerative colitis and Crohn's disease, affect several million individuals worldwide. These diseases are...

Screening of Potential Biomarkers in the Peripheral Serum for Steroid-Induced Osteonecrosis of the Femoral Head Based on WGCNA and Machine Learning Algorithms.

BACKGROUND: Steroid-induced osteonecrosis of the femoral head (SONFH) has produced a substantial burden of medical and social experience. However, the...

Development and validation of a deep learning-based algorithm for colonoscopy quality assessment.

BACKGROUND: Quality indicators should be assessed and monitored to improve colonoscopy quality in clinical practice. Endoscopists must enter relevant ...

Computational models in inflammatory bowel disease.

Inflammatory bowel disease (IBD) is a chronic and relapsing disease with multiple underlying influences and notable heterogeneity among its clinical a...

Dietary Inhibitors of CYP3A4 Are Revealed Using Virtual Screening by Using a New Deep-Learning Classifier.

CYP3A4 is the main human enzyme responsible for phase I metabolism of dietary compounds, prescribed drugs and xenobiotics, steroid hormones, and bile ...

Colonoscopic image synthesis with generative adversarial network for enhanced detection of sessile serrated lesions using convolutional neural network.

Computer-aided detection (CADe) systems have been actively researched for polyp detection in colonoscopy. To be an effective system, it is important t...

Relationship between vedolizumab serum concentrations in the induction phase and early and sustained response in the first year of treatment in patients with ulcerative colitis.

OBJECTIVE: Evidence on the usefulness of proactive monitoring of vedolizumab serum concentrations during the induction phase of treatment is limited. ...

Effects of nano-manganese on humoral immune response and oxidative stress in broilers.

The objective of the present study was to evaluate the alterations in selected indicators of immune responses and oxidative stress of broilers fed wit...

Artificial intelligence and inflammatory bowel disease: practicalities and future prospects.

Artificial intelligence (AI) is an emerging technology predicted to have significant applications in healthcare. This review highlights AI application...

Adrenal Insufficiency: Investigating Prevalence and Healthcare Utilization Using Administrative Data.

CONTEXT: Adrenal insufficiency (AI) is an uncommon, life-threatening disorder requiring lifelong treatment with steroid therapy and special attention ...

Artificial intelligence for the assessment of bowel preparation.

BACKGROUND AND AIMS: A reliable assessment of bowel preparation is important to ensure high-quality colonoscopy. Current bowel preparation scoring sys...

Identifying Microbe-Disease Association Based on a Novel Back-Propagation Neural Network Model.

Over the years, numerous evidences have demonstrated that microbes living in the human body are closely related to human life activities and human dis...

Deep reconstruction-recoding network for unsupervised domain adaptation and multi-center generalization in colonoscopy polyp detection.

BACKGROUND AND OBJECTIVE: Currently, the best performing methods in colonoscopy polyp detection are primarily based on deep neural networks (DNNs), wh...

Deep neural network for video colonoscopy of ulcerative colitis: a cross-sectional study.

BACKGROUND: A combination of endoscopic and histological evaluation is important in the management of patients with ulcerative colitis. We aimed to ad...