Inflammatory Bowel Disease

IBD: An Interpretable Backdoor-Detection Method via Multivariate Interactions.

Recent work has shown that deep neural networks are vulnerable to backdoor attacks. In comparison wi...

Molecular Networking and On-Tissue Chemical Derivatization for Enhanced Identification and Visualization of Steroid Glycosides by MALDI Mass Spectrometry Imaging.

Spatial metabolomics describes the spatially resolved analysis of interconnected pathways, biochemic...

A novel application of neural networks to identify potentially effective combinations of biologic factors for enhancement of bone fusion/repair.

INTRODUCTION: The use of biologic adjuvants (orthobiologics) is becoming commonplace in orthopaedic ...

Artificial Intelligence and Deep Learning for Rheumatologists.

Deep learning has emerged as the leading method in machine learning, spawning a rapidly growing fiel...

Automated classification of estrous stage in rodents using deep learning.

The rodent estrous cycle modulates a range of biological functions, from gene expression to behavior...

Robot-assisted laparoscopic surgery with a fluorescent near-infrared ray ureteral catheter for a rectal cancer patient with pelvic kidney: A case report.

An 85-year-old woman presented with a stomachache after a meal and was admitted to the previous clin...

New endoscopic tools in inflammatory bowel disease.

Endoscopic remission is now considered the ultimate long-term goal for treating inflammatory bowel d...

Deep learning-based automated quantification of goblet cell mucus using histological images as a predictor of clinical relapse of ulcerative colitis with endoscopic remission.

BACKGROUND: Mucin depletion is one of the histological indicators of clinical relapse among patients...

Deep Learning-Based Nuclear Morphometry Reveals an Independent Prognostic Factor in Mantle Cell Lymphoma.

Blastoid/pleomorphic morphology is associated with short survival in mantle cell lymphoma (MCL), but...

A Model of Normality Inspired Deep Learning Framework for Depression Relapse Prediction Using Audiovisual Data.

BACKGROUND: Depression (Major Depressive Disorder) is one of the most common mental illnesses. Accor...

RCMNet: A deep learning model assists CAR-T therapy for leukemia.

Acute leukemia is a type of blood cancer with a high mortality rate. Current therapeutic methods inc...

Comprehensive review of publicly available colonoscopic imaging databases for artificial intelligence research: availability, accessibility, and usability.

BACKGROUND AND AIMS: Publicly available databases containing colonoscopic imaging data are valuable ...

Acute colonic flexures: the basis for developing an artificial intelligence-based tool for predicting the course of colonoscopy.

Tortuosity of the colon is an important parameter for predicting the course of colonoscopy. Computed...

Deep learning-based approach to the characterization and quantification of histopathology in mouse models of colitis.

Inflammatory bowel disease (IBD) is a chronic immune-mediated disease of the gastrointestinal tract....

UC-NfNet: Deep learning-enabled assessment of ulcerative colitis from colonoscopy images.

Ulcerative colitis (UC) belongs to the inflammatory bowel disease (IBD) family, which is mainly caus...

Robust automated prediction of the revised Vienna Classification in colonoscopy using deep learning: development and initial external validation.

BACKGROUND: Improved optical diagnostic technology is needed that can be used by also outside expert...

Deep Learning-Based CT Imaging in the Diagnosis of Treatment Effect of Pulmonary Nodules and Radiofrequency Ablation.

To study the effect of computerized tomography (CT) images based on deep learning algorithms on the ...

Artificial Intelligence for Colonoscopy: Past, Present, and Future.

During the past decades, many automated image analysis methods have been developed for colonoscopy. ...

Double-Balanced Loss for Imbalanced Colorectal Lesion Classification.

Colorectal cancer has a high incidence rate in all countries around the world, and the survival rate...

Automated histological classification for digital pathology images of colonoscopy specimen via deep learning.

Colonoscopy is an effective tool to detect colorectal lesions and needs the support of pathological ...

Prediction of vedolizumab treatment outcomes by machine learning.