GERD

The use of artificial intelligence in colonoscopic evaluations.

PURPOSE OF REVIEW: This review aims to highlight the transformative impact of artificial intelligence in the field of gastrointestinal endoscopy, particularly in the detection and characterization of colorectal polyps.

Key genes and pathways in the molecular landscape of pancreatic ductal adenocarcinoma: A bioinformatics and machine learning study.

Pancreatic ductal adenocarcinoma (PDAC) is recognized for its aggressive nature, dismal prognosis, and a notably low five-year survival rate, underscoring the critical need for early detection methods and more effective therapeutic approaches. This research rigorously investigates the molecular mechanisms underlying PDAC, with a focus on the identification of pivotal genes and pathways that may ho...

How do medical students perceive the role of artificial intelligence in management of gastroesophageal reflux disease?

BACKGROUND: Artificial intelligence (AI) has significantly revolutionized the diagnosis and treatment of various medical and surgical conditions, incl...

Patient public perspectives on digital colorectal cancer surgery (DALLAS).

INTRODUCTION: The importance of patient perspectives is increasingly appreciated in clinical practice and academia with formal engagement processes de...

Identifying the Severity of Heart Valve Stenosis and Regurgitation Among a Diverse Population Within an Integrated Health Care System: Natural Language Processing Approach.

BACKGROUND: Valvular heart disease (VHD) is a leading cause of cardiovascular morbidity and mortality that poses a substantial health care and economi...

Development and application of an artificial intelligence-assisted endoscopy system for diagnosis of Helicobacter pylori infection: a multicenter randomized controlled study.

BACKGROUND: The early diagnosis and treatment of Heliobacter pylori (H.pylori) gastrointestinal infection provide significant benefits to patients. We...

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 computing hardware can interface with existing nasal...

Artificial Intelligence in Gastrointestinal Endoscopy.

Recent advancements in artificial intelligence (AI) have significantly impacted the field of gastrointestinal (GI) endoscopy, with applications spanni...

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 monitoring digestive tract diseases. However, the analys...

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 Networks (GNNs) to classify diseases, incorporating Human...

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 though many diverse sorts of data and machine learn...

Will Transformers change gastrointestinal endoscopic image analysis? A comparative analysis between CNNs and Transformers, in terms of performance, robustness and generalization.

Gastrointestinal endoscopic image analysis presents significant challenges, such as considerable variations in quality due to the challenging in-body ...

Artificial Intelligence and Mitral Regurgitation: Friend or Foe?

Systems Biology and Machine Learning Identify Genetic Overlaps Between Lung Cancer and Gastroesophageal Reflux Disease.

One Health and planetary health place emphasis on the common molecular mechanisms that connect several complex human diseases as well as human and pla...

Building Machine Learning Models in Gastrointestinal Endoscopy.

The current landscape of machine learning models in GI endoscopy is fraught with considerable variability in methodologies and quality, posing challen...

Deep learning approach for dysphagia detection by syllable-based speech analysis with daily conversations.

Dysphagia, a disorder affecting the ability to swallow, has a high prevalence among the older adults and can lead to serious health complications. The...

Predictors of residual tricuspid regurgitation after interventional therapy: an automated deep-learning CT analysis.

Computed tomography (CT) is used as a valuable tool for device selection for interventional therapy in tricuspid regurgitation (TR). We aimed to evalu...

Role of artificial intelligence in Crohn's disease intestinal strictures and fibrosis.

Crohn's disease (CD) is a chronic inflammatory disorder of the gastrointestinal tract. Intestinal fibrosis or stricture is one of the most prevalent c...

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

Obtaining accurate distance or depth information in endoscopy is crucial for the effective utilization of navigation systems. However, due to space co...

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. Endoscopy imaging of horse throat is a gold standard fo...