Gastroenterology

Peptic Ulcer Disease

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

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Real-time augmentation of diagnostic nasal endoscopy video using AI-enabled edge computing.

AI-enabled augmentation of nasal endoscopy video images is feasible in the clinical setting. Edge co...

Artificial Intelligence in Gastrointestinal Endoscopy.

Recent advancements in artificial intelligence (AI) have significantly impacted the field of gastroi...

Review of Deep Learning Performance in Wireless Capsule Endoscopy Images for GI Disease Classification.

Wireless capsule endoscopy is a non-invasive medical imaging modality used for diagnosing and monito...

A review of machine learning methods for non-invasive blood pressure estimation.

Blood pressure is a very important clinical measurement, offering valuable insights into the hemodyn...

Coagulo-Net: Enhancing the mathematical modeling of blood coagulation using physics-informed neural networks.

Blood coagulation, which involves a group of complex biochemical reactions, is a crucial step in hem...

Collaborative weighting in federated graph neural networks for disease classification with the human-in-the-loop.

The authors introduce a novel framework that integrates federated learning with Graph Neural Network...

Intelligence model on sequence-based prediction of PPI using AISSO deep concept with hyperparameter tuning process.

Protein-protein interaction (PPI) prediction is vital for interpreting biological activities. Even t...

Magnetic Torque-Driven All-Terrain Microrobots.

All-terrain microrobots possess significant potential in modern medical applications due to their su...

ARViS: a bleed-free multi-site automated injection robot for accurate, fast, and dense delivery of virus to mouse and marmoset cerebral cortex.

Genetically encoded fluorescent sensors continue to be developed and improved. If they could be expr...

Building Machine Learning Models in Gastrointestinal Endoscopy.

The current landscape of machine learning models in GI endoscopy is fraught with considerable variab...

Hematoma expansion prediction in intracerebral hemorrhage patients by using synthesized CT images in an end-to-end deep learning framework.

Spontaneous intracerebral hemorrhage (ICH) is a type of stroke less prevalent than ischemic stroke b...

Early prognosis prediction for non-variceal upper gastrointestinal bleeding in the intensive care unit: based on interpretable machine learning.

INTRODUCTION: This study aims to construct a mortality prediction model for patients with non-varice...

Depth estimation from monocular endoscopy using simulation and image transfer approach.

Obtaining accurate distance or depth information in endoscopy is crucial for the effective utilizati...

Explainable machine learning for assessing upper respiratory tract of racehorses from endoscopy videos.

Laryngeal hemiplegia (LH) is a major upper respiratory tract (URT) complication in racehorses. Endos...

Applying 12 machine learning algorithms and Non-negative Matrix Factorization for robust prediction of lupus nephritis.

Lupus nephritis (LN) is a challenging condition with limited diagnostic and treatment options. In th...

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