Peptic Ulcer Disease

Correspondence on "Evaluation of the impact of NOAC underdosing and exploration of bleeding risk factors in elderly patients with atrial fibrillation: artificial intelligence-based approach" by Protzenko et al.

Integrating Artificial Intelligence into Endoscopy Training.

As artificial intelligence (AI) becomes integrated into gastrointestinal endoscopy, training programs must adapt to prepare learners for AI-assisted practice. This review outlines current AI applications, ranging from polyp detection to workflow analysis, and proposes a structured curriculum embedding AI at every stage of training. The framework aims for both technical proficiency and adaptive exp...

An AI-based approach accelerates the discovery of protein-protein interaction modulators targeting NCS-1.

Drug repurposing is an efficient strategy to accelerate the identification of therapeutic compounds by finding new uses for existing drugs. Here, we l...

Development and validation of a multimodal deep learning model for early esophageal squamous neoplasia detection and invasion depth prediction.

Early detection of esophageal squamous cell carcinoma (ESCC) is critical for optimizing patient outcomes. Magnifying endoscopy and endoscopic ultrason...

Solution-Processed Optoelectronic Fusion-Upconversion Devices for Intelligent Perception and Communication.

The rapid growth of the artificial intelligence of things (AIoT) demands multifunctional sensors that deliver intuitive visuals and machine-readable s...

Digital Microscopy in the Endoscopy Suite: A Reference Standard for Colorectal Polyp Size Measurement.

BACKGROUND AND STUDY AIMS: Accurate determination of colorectal polyp size is critical for surveillance recommendations and for generating reliable gr...

Explainable machine learning predicts mortality in critically ill patients with nonvariceal upper gastrointestinal bleeding: a MIMIC-IV study with external validation.

A predictive model for significant periodontal disease progression: A large-scale cohort study.

BACKGROUND: The progression of periodontitis is challenging to predict. This study aimed to develop and validate a machine learning model to identify ...

Machine Learning in Assessing Intraoperative Blood Loss: A Systematic Review and Meta-Analysis.

AIM: To evaluate the value of machine learning in assessing intraoperative blood loss by comparing associated outcomes with those of the gold standard...

Integrated Single-Cell and Bulk Transcriptome Analysis Reveals the Prognostic Significance and Immune Regulatory Mechanisms of Sialylation in Hepatocellular Carcinoma.

Liver Hepatocellular Carcinoma (LIHC) is a high-mortality primary liver cancer. Its treatment and prognosis are highly dependent on disease stage and ...

Evaluating the cost-effectiveness of artificial intelligence in Barrett's surveillance.

Artificial intelligence (AI) has emerged as a promising tool to detect early dysplasia in Barrett's esophagus (BE). However, the cost-effectiveness of...

Machine learning estimation of FVIII pharmacokinetic parameters in Chinese children with severe Hemophilia A.

Hemophilia A is a rare inherited bleeding disorder typically managed with coagulation factor VIII (FVIII) replacement therapy. Designing personalized ...

Machine learning-based identification of potential diagnostic signatures in spinal cord injury.

STUDY DESIGN: Bioinformatics analysis. OBJECTIVES: To explore the diagnostic signatures for patients with spinal cord injury (SCI). SETTING: Shenyang,...

Identification of extracellular matrix stiffness-related genes in human scleral fibroblasts through bioinformatics analysis and machine learning.

BACKGROUND: Scleral extracellular matrix (ECM) remodeling plays a key role in myopia development. This study aims to identify ECM stiffness-related ge...

Integrating Clinical Modeling and Machine Learning for Risk Assessment of Paracetamol and Other Nonsteroidal Anti-Inflammatory Drug Hypersensitivity in Children.

BACKGROUND: Nonsteroidal anti-inflammatory drug (NSAID) hypersensitivity is a common cause of drug-related reactions in children. Pre-test risk strati...

CystoDS: a multiclass endoscopy image dataset for artificial intelligence-assisted bladder cancer detection.

Cystoscopy is a common endoscopic procedure used for the visual inspection of the lower urinary tract, particularly for the detection and surveillance...

Ensemble model assisted classification of gastrointestinal bleeding using wireless capsule endoscopy.

Wireless Capsule Endoscopy (WCE) is a useful method for imaging the intestines painlessly and looking into gastrointestinal tract diseases. The invest...

Generative AI Uncovers Novel Chrebp/Txnip Axis Inhibitors with Potential Anti-inflammatory Activity.

Type 2 diabetes is driven in part by metabolic inflammation, where activation of the Chrebp/Txnip axis promotes NLRP3 inflammasome assembly, leading t...

Diagnosis of Gastric Intestinal Metaplasia: Histology, Endoscopy, and Artificial Intelligence.

Background Gastric intestinal metaplasia (GIM) is a well-established precancerous lesion and key biomarker for assessing the risk of gastric cancer. H...

Endoscopic Ultrasound for the Management of Pancreatic Neuroendocrine Tumors: Diagnosis, Treatment, and Future Perspectives.

Pancreatic neuroendocrine tumors (PanNETs) are increasingly diagnosed, reflecting greater clinical awareness, improved imaging, and revised classifica...