Gastroenterology

Peptic Ulcer Disease

Latest AI and machine learning research in peptic ulcer disease for healthcare professionals.

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Showing 169-189 of 3,581 articles
Machine Learning of Endoscopy Images to Identify, Classify, and Segment Sinonasal Masses.

BACKGROUND: We developed and assessed the performance of a machine learning model (MLM) to identify,...

MAGPIE: A Machine Learning Approach to Decipher Protein-Protein Interactions in Human Plasma.

Immunoprecipitation coupled to tandem mass spectrometry (IP-MS/MS) methods are often used to identif...

A Plasma Proteomics-Based Model for Identifying the Risk of Postpartum Depression Using Machine Learning.

Postpartum depression (PPD) poses significant risks to maternal and infant health, yet proteomic ana...

Meta-Learning Enables Complex Cluster-Specific Few-Shot Binding Affinity Prediction for Protein-Protein Interactions.

Predicting protein-protein interaction (PPI) binding affinities in unseen protein complex clusters i...

The clinical features and risk factors of coagulopathy associated with cefoperazone/sulbactam: a nomogram prediction model.

BACKGROUND: Cefoperazone/sulbactam (CPZ/SAM) is an important treatment option for infections caused ...

Deciphering Necroptosis-Associated Molecular Subtypes in Acute Ischemic Stroke Through Bioinformatics and Machine Learning Analysis.

Acute ischemic stroke (AIS) is a severe disorder characterized by complex pathophysiological process...

Analysis of diagnostic genes and molecular mechanisms of Crohn's disease and colon cancer based on machine learning algorithms.

Crohn's disease (CD) is a chronic inflammatory bowel condition, and colon adenocarcinoma (COAD), as ...

Artificial intelligence in pancreaticobiliary endoscopy: Current applications and future directions.

Pancreaticobiliary endoscopy is an essential tool for diagnosing and treating pancreaticobiliary dis...

Interpretable machine learning-driven biomarker identification and validation for Alzheimer's disease.

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by limited effective treatmen...

Predicting candidate biomarkers for COVID-19 associated with leukemia in children.

Since the COVID-19 pandemic, a significant number of pediatric leukemia patients have shown to have ...

Application of artificial intelligence in gastrointestinal endoscopy in Vietnam: a narrative review.

The utilization of artificial intelligence (AI) in gastrointestinal (GI) endoscopy has witnessed sig...

Application of machine learning methods for predicting esophageal variceal bleeding in patients with cirrhosis.

OBJECTIVE: To develop and compare machine learning models based on CT morphology features, serum bio...

Deep representation learning of protein-protein interaction networks for enhanced pattern discovery.

Protein-protein interaction (PPI) networks, where nodes represent proteins and edges depict myriad i...

Novel artificial intelligence-based identification of drug-gene-disease interaction using protein-protein interaction.

The evaluation of drug-gene-disease interactions is key for the identification of drugs effective ag...

Spontaneous Hepatic Rupture Complicating Preeclampsia and HELLP Syndrome: A Case Report.

Spontaneous hepatic rupture is a rare complication that occurs in pregnant mothers with HELLP syndr...

QUAIDE - Quality assessment of AI preclinical studies in diagnostic endoscopy.

Artificial intelligence (AI) holds significant potential for enhancing quality of gastrointestinal (...

An End-to-End Knowledge Graph Fused Graph Neural Network for Accurate Protein-Protein Interactions Prediction.

Protein-protein interactions (PPIs) are essential to understanding cellular mechanisms, signaling ne...

RGCNPPIS: A Residual Graph Convolutional Network for Protein-Protein Interaction Site Prediction.

Accurate identification of protein-protein interaction (PPI) sites is crucial for understanding the ...

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