Inflammatory Bowel Disease

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 heterogeneous at the clinical, immunological and genetic levels and result from complex host and environmental interactions. Investigating drug efficacy for IBD can improve our understanding of why treatment response can vary between patients. We pr...

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 current diagnosis is still limited. Thus, this study is aimed at identifying potential biomarkers in the peripheral serum of patients with SONFH.

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...

Discovery of Pyrazolo[3,4-]pyridazinone Derivatives as Selective DDR1 Inhibitors via Deep Learning Based Design, Synthesis, and Biological Evaluation.

Alterations of discoidin domain receptor1 (DDR1) may lead to increased production of inflammatory cytokines, making DDR1 an attractive target for infl...

Efficacy of Platelet-Rich Plasma as an Adjuvant Therapy to Endoscopic Sinus Surgery in Anosmia Patients with Sinonasal Polyposis: A Randomized Controlled Clinical Trial.

Treatment of patients with anosmia is a major therapeutic challenge. The present study evaluated the efficacy of platelet-rich plasma (PRP) in the tr...

Detection of colorectal lesions during colonoscopy.

Owing to its high mortality rate, the prevention of colorectal cancer is of particular importance. The resection of colorectal polyps is reported to d...

Evaluation of an Artificial Intelligence-Augmented Digital System for Histologic Classification of Colorectal Polyps.

IMPORTANCE: Colorectal polyps are common, and their histopathologic classification is used in the planning of follow-up surveillance. Substantial vari...

Deep Learning for Prediction of N2 Metastasis and Survival for Clinical Stage I Non-Small Cell Lung Cancer.

Background Preoperative mediastinal staging is crucial for the optimal management of clinical stage I non-small cell lung cancer (NSCLC). Purpose To d...

Association of TLR 9 gene polymorphisms with remission in patients with rheumatoid arthritis receiving TNF-α inhibitors and development of machine learning models.

Toll-like receptor (TLR)-4 and TLR9 are known to play important roles in the immune system, and several studies have shown their association with the ...