Gastroenterology

Advancement of artificial intelligence systems for surveillance endoscopy of Barrett's esophagus.

Barrett's esophagus (BE) is a precursor disease for esophageal adenocarcinoma. Timely detection and treatment has significant influence on patient outcomes. Over the last years, several artificial intelligence (AI) systems have emerged to assist the endoscopist. The primary focus of research has been computer aided detection (CADe). Several groups have succeeded in developing competitive models fo...

Fixed, Dilated, and Cannulated - Medical Management of Elevated Intracranial Pressures due to a Large Intracranial Hemorrhage in a Patient on Veno-Venous Extracorporeal Membrane Oxygenation: Case Report.

A 40-year-old woman presented with mediastinitis, necrotizing pancreatitis, and severe acute respiratory distress syndrome with refractory acidemia (pH 7.14) and hypercapnia (PaCO 115 mmHg), requiring veno-venous extracorporeal membrane oxygenation (ECMO). Eight hours after cannulation, and rapid correction of PaCO to 44 mmHg, she was found to have bilaterally fixed and dilated pupils. Imaging sho...

Artificial intelligence-aided diagnostic imaging: A state-of-the-art technique in precancerous screening.

BACKGROUND AND AIM: Chromoendoscopy with the use of indigo carmine (IC) dye is a crucial endoscopic technique to identify gastrointestinal neoplasms. ...

CEMRI-Based Quantification of Intratumoral Heterogeneity for Predicting Aggressive Characteristics of Hepatocellular Carcinoma Using Habitat Analysis: Comparison and Combination of Deep Learning.

RATIONALE AND OBJECTIVES: To explore both an intratumoral heterogeneity (ITH) model based on habitat analysis and a deep learning (DL) model based on ...

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 disease (CD). However, CD misdiagnosis frequently...

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 antibiotic substitutes. As a result, the purpose of the ...

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.].

Application of artificial intelligence in endoscopic gastrointestinal tumors.

With an increasing number of patients with gastrointestinal cancer, effective and accurate early diagnostic clinical tools are required provide better...

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 landmark for clinical decision making. Artificial inte...

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 chemotherapy outcomes in gastric cancer (GC). Yet, ...

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 time after administration of the contrast agent. Th...

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 inflammatory bowel disease (IBD). We aimed to descri...

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

Conventional catheter- or probe-based in vivo biomedical sensing is uncomfortable, inconvenient, and sometimes infeasible for long-term monitoring. Ex...

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 grade 3 (G3) pancreatic neuroendocrine tumors (PNE...

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" measuring predicted longevity and enable the quanti...

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

OBJECTIVES: High-resolution manometry (HRM) and esophagography are used for achalasia diagnosis; however, achalasia phenotypes combining esophageal mo...

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 have higher transfusion requirements, uncontrolled bl...

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 predicting high-grade small bowel obstruction (HGSBO).

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, and pancreatic cancer, poses a challenge and, as a...

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 volume (TTV) in patients with colorectal liver metast...