Inflammatory Bowel Disease

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 pl...

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 ...

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 seve...

A Deep Learning Approach for Colonoscopy Pathology WSI Analysis: Accurate Segmentation and Classification.

Colorectal cancer (CRC) is one of the most life-threatening malignancies. Colonoscopy pathology exam...

Mutual-Prototype Adaptation for Cross-Domain Polyp Segmentation.

Accurate segmentation of the polyps from colonoscopy images provides useful information for the diag...

Perioperative Outcomes of a Hydrocortisone Protocol after Endonasal Surgery for Pituitary Adenoma Resection.

 In pituitary adenomas (PAs), the use of postoperative steroid supplementation remains controversia...

Role of Digital Health and Artificial Intelligence in Inflammatory Bowel Disease: A Scoping Review.

Inflammatory bowel diseases (IBD), subdivided into Crohn's disease (CD) and ulcerative colitis (UC),...

Machine Learning Modeling from Omics Data as Prospective Tool for Improvement of Inflammatory Bowel Disease Diagnosis and Clinical Classifications.

Research of inflammatory bowel disease (IBD) has identified numerous molecular players involved in t...

Multi-step validation of a deep learning-based system for the quantification of bowel preparation: a prospective, observational study.

BACKGROUND: Inadequate bowel preparation is associated with a decrease in adenoma detection rate (AD...

Deep learning for automated bowel preparation assessment during colonoscopy: time to embrace a new approach?

Deep Learning Computer-aided Polyp Detection Reduces Adenoma Miss Rate: A United States Multi-center Randomized Tandem Colonoscopy Study (CADeT-CS Trial).

BACKGROUND & AIMS: Artificial intelligence-based computer-aided polyp detection (CADe) systems are i...

Colorectal Polyp Image Detection and Classification through Grayscale Images and Deep Learning.

Colonoscopy screening and colonoscopic polypectomy can decrease the incidence and mortality rate of ...

Artificial intelligence-assisted colonoscopy: A prospective, multicenter, randomized controlled trial of polyp detection.

BACKGROUND: Artificial intelligence (AI) assistance has been considered as a promising way to improv...

HOX cluster and their cofactors showed an altered expression pattern in eutopic and ectopic endometriosis tissues.

Endometriosis is major gynecological disease that affects over 10% of women worldwide and 30%-50% of...

Defining the next steps for artificial intelligence in colonoscopy.

Losartan as a Steroid-Sparing Adjunct in a Patient With Features of Refractory Camurati-Engelmann Disease.

OBJECTIVE: The treatment of Camurati-Engelmann disease (CED) involves the use of glucocorticoids, an...

Automatic Polyp Segmentation in Colonoscopy Images Using a Modified Deep Convolutional Encoder-Decoder Architecture.

Colorectal cancer has become the third most commonly diagnosed form of cancer, and has the second hi...

Artificial intelligence and polyp detection in colonoscopy: Use of a single neural network to achieve rapid polyp localization for clinical use.

BACKGROUND AND AIM: Artificial intelligence has been extensively studied to assist clinicians in pol...

A machine learning approach identifies 5-ASA and ulcerative colitis as being linked with higher COVID-19 mortality in patients with IBD.

Inflammatory bowel diseases (IBD), namely Crohn's disease (CD) and ulcerative colitis (UC) are chron...

Machine learning using clinical data at baseline predicts the efficacy of vedolizumab at week 22 in patients with ulcerative colitis.

Predicting the response of patients with ulcerative colitis (UC) to a biologic such as vedolizumab (...

Robotic Assay for Drought (RoAD): an automated phenotyping system for brassinosteroid and drought responses.

Brassinosteroids (BRs) are a group of plant steroid hormones involved in regulating growth, developm...