Gastroenterology

Artificial Intelligence-based Segmentation of Residual Pancreatic Cancer in Resection Specimens Following Neoadjuvant Treatment (ISGPP-2): International Improvement and Validation Study.

Neoadjuvant therapy (NAT) has become routine in patients with borderline resectable pancreatic cance...

ESCCPred: a machine learning model for diagnostic prediction of early esophageal squamous cell carcinoma using autoantibody profiles.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is a deadly cancer with no clinically ideal bi...

Deep learning classification of ex vivo human colon tissues using spectroscopic optical coherence tomography.

Screening for colorectal cancer (CRC) with colonoscopy has improved patient outcomes; however, it re...

An artificial intelligence system for comprehensive pathologic outcome prediction in early gastric cancer through endoscopic image analysis (with video).

BACKGROUND: Accurate prediction of pathologic results for early gastric cancer (EGC) based on endosc...

ASO Author Reflections: Development and Validation Study of the Prognostic Impact of Deep Learning-Determined Myxoid Stroma After Neoadjuvant Chemotherapy in Patients with Esophageal Squamous Cell Carcinoma.

Localized fine-tuning and clinical evaluation of deep-learning based auto-segmentation (DLAS) model for clinical target volume (CTV) and organs-at-risk (OAR) in rectal cancer radiotherapy.

BACKGROUND AND PURPOSE: Various deep learning auto-segmentation (DLAS) models have been proposed, so...

Machine learning methods in automated detection of CT enterography findings in Crohn's disease: A feasibility study.

PURPOSE: Qualitative findings in Crohn's disease (CD) can be challenging to reliably report and quan...

Deep learning analysis for differential diagnosis and risk classification of gastrointestinal tumors.

OBJECTIVES: Recently, artificial intelligence (AI) has been applied to clinical diagnosis. Although ...

Diagnosing Solid Lesions in the Pancreas With Multimodal Artificial Intelligence: A Randomized Crossover Trial.

IMPORTANCE: Diagnosing solid lesions in the pancreas via endoscopic ultrasonographic (EUS) images is...

Rapid diagnosis of celiac disease based on plasma Raman spectroscopy combined with deep learning.

Celiac Disease (CD) is a primary malabsorption syndrome resulting from the interplay of genetic, imm...

Exploration and verification a 13-gene diagnostic framework for ulcerative colitis across multiple platforms via machine learning algorithms.

Ulcerative colitis (UC) is a chronic inflammatory bowel disease with intricate pathogenesis and vari...

Prediction of in-hospital Mortality of Intensive Care Unit Patients with Acute Pancreatitis Based on an Explainable Machine Learning Algorithm.

BACKGROUND AND AIM: Acute pancreatitis (AP) is potentially fatal. Therefore, early identification of...

Differentiating Gastrointestinal Stromal Tumors From Leiomyomas of Upper Digestive Tract Using Convolutional Neural Network Model by Endoscopic Ultrasonography.

BACKGROUND: Gastrointestinal stromal tumors (GISTs) and leiomyomas are the most common submucosal tu...

Morphometric analysis and tortuosity typing of the large intestine segments on computed tomography colonography with artificial intelligence.

BACKGROUND: Morphological properties such as length and tortuosity of the large intestine segments p...

Artificial intelligence-assisted identification and retrieval of chronic hepatitis C patients lost to follow-up in the health area of Pontevedra and O Salnés (Spain).

OBJECTIVE: Direct-acting antivirals (DAAs) to treat hepatitis C virus (HCV) infection offer an oppor...

A Comparison of CT-Based Pancreatic Segmentation Deep Learning Models.

RATIONALE AND OBJECTIVES: Pancreas segmentation accuracy at CT is critical for the identification of...

Ultra-high resolution computed tomography with deep-learning-reconstruction: diagnostic ability in the assessment of gastric cancer and the depth of invasion.

PURPOSE: To evaluate the image quality of ultra-high-resolution CT (U-HRCT) images reconstructed usi...

GLGFormer: Global Local Guidance Network for Mucosal Lesion Segmentation in Gastrointestinal Endoscopy Images.

Automatic mucosal lesion segmentation is a critical component in computer-aided clinical support sys...

LightGBM is an Effective Predictive Model for Postoperative Complications in Gastric Cancer: A Study Integrating Radiomics with Ensemble Learning.

Postoperative complications of radical gastrectomy seriously affect postoperative recovery and requi...

Machine learning methods for unveiling the potential of antioxidant short peptides in goat milk-derived proteins during in vitro gastrointestinal digestion.

Milk serves as an important dietary source of bioactive peptides, offering notable benefits to indiv...

Explainable AI based automated segmentation and multi-stage classification of gastroesophageal reflux using machine learning techniques.

Presently, close to two million patients globally succumb to gastrointestinal reflux diseases (GERD)...