Gastroenterology

Deep learning-based lesion detection and severity grading of small-bowel Crohn's disease ulcers on double-balloon endoscopy images.

BACKGROUND AND AIMS: Double-balloon endoscopy (DBE) is widely used in diagnosing small-bowel Crohn's...

The potential of Spirulina platensis to substitute antibiotics in Japanese quail diets: impacts on growth, carcass traits, antioxidant status, blood biochemical parameters, and cecal microorganisms.

The development of antibiotic-resistant microorganisms prompted the investigation of possible antibi...

Application of artificial intelligence in endoscopic gastrointestinal tumors.

With an increasing number of patients with gastrointestinal cancer, effective and accurate early dia...

Retracted: Artificial Intelligence Algorithm-Based CTA Imaging for Diagnosing Ischemic Type Biliary Lesions after Orthotopic Liver Transplantation.

[This retracts the article DOI: 10.1155/2022/3399892.].

Retracted: Ultrasound Image-Guided Nerve Block Combined with General Anesthesia under an Artificial Intelligence Algorithm on Patients Undergoing Radical Gastrectomy for Gastric Cancer during and after Operation.

[This retracts the article DOI: 10.1155/2022/6914157.].

Can artificial intelligence replace endoscopists when assessing mucosal healing in ulcerative colitis? A systematic review and diagnostic test accuracy meta-analysis.

BACKGROUNDS AND AIMS: Mucosal healing (MH) in inflammatory bowel diseases (IBD) is an important land...

Diagnostic accuracy of radiomics-based machine learning for neoadjuvant chemotherapy response and survival prediction in gastric cancer patients: A systematic review and meta-analysis.

BACKGROUND: In recent years, researchers have explored the use of radiomics to predict neoadjuvant c...

Effectiveness of strategies to suppress antibodies to infliximab in pediatric inflammatory bowel disease.

OBJECTIVES: Antibodies to infliximab (ATIs) are associated with loss of response in children with in...

Deep learning approach for discrimination of liver lesions using nine time-phase images of contrast-enhanced ultrasound.

PURPOSE: Contrast-enhanced ultrasound (CEUS) shows different enhancement patterns depending on the t...

Bio-Inspired Untethered Robot-Sensor Platform for Minimally Invasive Biomedical Sensing.

Conventional catheter- or probe-based in vivo biomedical sensing is uncomfortable, inconvenient, and...

Machine Learning Methods Based on CT Features Differentiate G1/G2 From G3 Pancreatic Neuroendocrine Tumors.

RATIONALE AND OBJECTIVES: To identify CT features for distinguishing grade 1 (G1)/grade 2 (G2) from ...

An accurate aging clock developed from large-scale gut microbiome and human gene expression data.

Accurate measurement of the biological markers of the aging process could provide an "aging clock" m...

Achalasia phenotypes and prediction of peroral endoscopic myotomy outcomes using machine learning.

OBJECTIVES: High-resolution manometry (HRM) and esophagography are used for achalasia diagnosis; how...

EUS coil and glue for gastric varices-prevent, treat and rescue, one therapy to rule them all?

BACKGROUND AND OBJECTIVES: In portal hypertension, gastric varix-associated bleeding is known to hav...

An easy-to-use artificial intelligence preoperative lymph node metastasis predictor (LN-MASTER) in rectal cancer based on a privacy-preserving computing platform: multicenter retrospective cohort study: erratum.

Deep learning models for automatic tumor segmentation and total tumor volume assessment in patients with colorectal liver metastases.

BACKGROUND: We developed models for tumor segmentation to automate the assessment of total tumor vol...

Artificial intelligence assisted endoscopic ultrasound for detection of pancreatic space-occupying lesion: a systematic review and meta-analysis.

BACKGROUND: Diagnosing pancreatic lesions, including chronic pancreatitis, autoimmune pancreatitis, ...

Deep learning using computed tomography to identify high-risk patients for acute small bowel obstruction: development and validation of a prediction model : a retrospective cohort study.

OBJECTIVE: To build a novel classifier using an optimized 3D-convolutional neural network for predic...

Deep learning-based attenuation correction method in Tc-GSA SPECT/CT hepatic imaging: a phantom study.

This study aimed to evaluate a deep learning-based attenuation correction (AC) method to generate ps...

Application of transfer learning to predict drug-induced human in vivo gene expression changes using rat in vitro and in vivo data.

The liver is the primary site for the metabolism and detoxification of many compounds, including pha...

Improved assessment of donor liver steatosis using Banff consensus recommendations and deep learning algorithms.

BACKGROUND & AIMS: The Banff Liver Working Group recently published consensus recommendations for st...