Inflammatory Bowel Disease

Diagnostic evaluation of a deep learning model for optical diagnosis of colorectal cancer.

Colonoscopy is commonly used to screen for colorectal cancer (CRC). We develop a deep learning model...

Regulatory considerations for artificial intelligence technologies in GI endoscopy.

Artificial intelligence (AI) technologies in clinical medicine have become the subject of intensive ...

Polyp detection algorithm can detect small polyps: Ex vivo reading test compared with endoscopists.

BACKGROUND AND STUDY AIMS: Small polyps are occasionally missed during colonoscopy. This study was c...

Predictors of remission from body dysmorphic disorder after internet-delivered cognitive behavior therapy: a machine learning approach.

BACKGROUND: Previous attempts to identify predictors of treatment outcomes in body dysmorphic disord...

What's new in IBD therapy: An "omics network" approach.

The industrial revolution that began in the late 1800s has resulted in dramatic changes in the envir...

Efficacy of Real-Time Computer-Aided Detection of Colorectal Neoplasia in a Randomized Trial.

BACKGROUND & AIMS: One-fourth of colorectal neoplasias are missed during screening colonoscopies; th...

Probing the degradation of pharmaceuticals in urine using MFC and studying their removal efficiency by UPLC-MS/MS.

Nutrient recovery from source-separated human urine has attracted interest as it is rich in nitrogen...

Deep learned tissue "fingerprints" classify breast cancers by ER/PR/Her2 status from H&E images.

Because histologic types are subjective and difficult to reproduce between pathologists, tissue morp...

The impact of deep convolutional neural network-based artificial intelligence on colonoscopy outcomes: A systematic review with meta-analysis.

BACKGROUND AND AIM: The utility of artificial intelligence (AI) in colonoscopy has gained popularity...

Gait-Based Machine Learning for Classifying Patients with Different Types of Mild Cognitive Impairment.

Mild cognitive impairment (MCI) may be caused by Alzheimer's disease, Parkinson's disease (PD), cere...

How Artificial Intelligence Will Impact Colonoscopy and Colorectal Screening.

Artificial intelligence may improve value in colonoscopy-based colorectal screening and surveillance...

Radiomics in gliomas: clinical implications of computational modeling and fractal-based analysis.

Radiomics is an emerging field that involves extraction and quantification of features from medical ...

Deep learning-based radiomic features for improving neoadjuvant chemoradiation response prediction in locally advanced rectal cancer.

Radiomic features achieve promising results in cancer diagnosis, treatment response prediction, and ...

Comparison of Serum Concentrations of Ustekinumab Obtained by Three Commercial Assays in Patients with Crohn's Disease.

BACKGROUND: Data on the association of ustekinumab (UST) drug concentrations and clinical outcomes a...

Multimodal neuroimaging-based prediction of adult outcomes in childhood-onset ADHD using ensemble learning techniques.

Attention-deficit/hyperactivity disorder (ADHD) is a highly prevalent and heterogeneous neurodevelop...

Interpretable Artificial Intelligence: Why and When.

The purpose of this article is to discuss the problem of interpretability of artificial intelligenc...

Big data in IBD: big progress for clinical practice.

IBD is a complex multifactorial inflammatory disease of the gut driven by extrinsic and intrinsic fa...

Deep learning uncertainty and confidence calibration for the five-class polyp classification from colonoscopy.

There are two challenges associated with the interpretability of deep learning models in medical ima...

Predicting individual clinical trajectories of depression with generative embedding.

Patients with major depressive disorder (MDD) show heterogeneous treatment response and highly varia...

Effect of a deep-learning computer-aided detection system on adenoma detection during colonoscopy (CADe-DB trial): a double-blind randomised study.

BACKGROUND: Colonoscopy with computer-aided detection (CADe) has been shown in non-blinded trials to...

Use of Artificial Intelligence-Based Analytics From Live Colonoscopies to Optimize the Quality of the Colonoscopy Examination in Real Time: Proof of Concept.