Inflammatory Bowel Disease

Colorectal polyp characterization with endocytoscopy: Ready for widespread implementation with artificial intelligence?

Endocytoscopy provides an in-vivo visualization of nuclei and micro-vessels at the cellular level in...

Impact of artificial intelligence on colorectal polyp detection.

Since colonoscopy and polypectomy were introduced, Colorectal Cancer (CRC) incidence and mortality d...

Population-Scale CT-based Body Composition Analysis of a Large Outpatient Population Using Deep Learning to Derive Age-, Sex-, and Race-specific Reference Curves.

Background Although CT-based body composition (BC) metrics may inform disease risk and outcomes, obt...

Using chatbots to screen for heritable cancer syndromes in patients undergoing routine colonoscopy.

BACKGROUND: Hereditary colorectal cancer (HCRC) syndromes account for 10% of colorectal cancers but ...

Resection of the medial wall of the cavernous sinus in functioning pituitary adenomas: Technical note and outcomes in a matched-cohort study.

BACKGROUND: Parasellar dural invasion can be associated with treatment failure after excision of fun...

A novel humanoid-robot simulator for colonoscopy.

Machine learning in predicting early remission in patients after surgical treatment of acromegaly: a multicenter study.

PURPOSE: Accurate prediction of postoperative remission is beneficial for effective patient-physicia...

A review of water exchange and artificial intelligence in improving adenoma detection.

Water exchange (WE) and artificial intelligence (AI) have made critical advances during the past dec...

Development and Interpretation of Multiple Machine Learning Models for Predicting Postoperative Delayed Remission of Acromegaly Patients During Long-Term Follow-Up.

Some patients with acromegaly do not reach the remission standard in the short term after surgery b...

Personalized prediction of daily eczema severity scores using a mechanistic machine learning model.

BACKGROUND: Atopic dermatitis (AD) is a chronic inflammatory skin disease with periods of flares and...

Application of optical character recognition with natural language processing for large-scale quality metric data extraction in colonoscopy reports.

BACKGROUND AND AIMS: Colonoscopy is commonly performed for colorectal cancer screening in the United...

Use of Steroid Profiling Combined With Machine Learning for Identification and Subtype Classification in Primary Aldosteronism.

IMPORTANCE: Most patients with primary aldosteronism, a major cause of secondary hypertension, are n...

HyperKvasir, a comprehensive multi-class image and video dataset for gastrointestinal endoscopy.

Artificial intelligence is currently a hot topic in medicine. However, medical data is often sparse ...

A novel machine learning strategy for model selections - Stepwise Support Vector Machine (StepSVM).

An essential aspect of medical research is the prediction for a health outcome and the scientific id...

Application of Deep Learning for Early Screening of Colorectal Precancerous Lesions under White Light Endoscopy.

METHODS: We collected and sorted out the white light endoscopic images of some patients undergoing c...

Endoscopic activity, tissue factor and Crohn's disease: findings in clinical remission patients.

BACKGROUND: As Crohn's disease (CD) is associated with a high risk of thromboembolic events (TE), in...

Deep learning to find colorectal polyps in colonoscopy: A systematic literature review.

Colorectal cancer has a great incidence rate worldwide, but its early detection significantly increa...

A Transparent and Adaptable Method to Extract Colonoscopy and Pathology Data Using Natural Language Processing.

Key variables recorded as text in colonoscopy and pathology reports have been extracted using natura...

An automated detection system for colonoscopy images using a dual encoder-decoder model.

Conventional computer-aided detection systems (CADs) for colonoscopic images utilize shape, texture,...

Structure equation model and neural network analyses to predict coronary artery lesions in Kawasaki disease: a single-centre retrospective study.

A new method to predict coronary artery lesions (CALs) in Kawasaki disease (KD) was developed using ...

Polyp Segmentation with Fully Convolutional Deep Neural Networks-Extended Evaluation Study.

Analysis of colonoscopy images plays a significant role in early detection of colorectal cancer. Aut...