GERD

Pretreatment Radiation Esophagitis Prediction Using Quantum Machine Learning in Patients With Esophageal Cancer.

PURPOSE: To introduce a hybrid quantum-classical machine learning approach and validate its feasibility and accuracy for pretreatment radiation-induced esophagitis (RE) prediction in patients with esophageal cancer undergoing radiation therapy or chemoradiotherapy. METHODS AND MATERIALS: This study enrolled 218 patients with esophageal cancer from hospital 1 for training and internal validation an...

A multi-toxicity deep learning approach for normal tissue complication probability modelling in head and neck cancer patients receiving radiotherapy.

PURPOSE: Toxicities after radiotherapy for head and neck cancer (HNC) often co-occur and share underlying mechanisms, yet most conventional and deep learning (DL) NTCP models predict only a single endpoint. By developing DL NTCP models which can predict multiple toxicities simultaneously, this study aimed to capture inter-toxicity relationships to improve prediction performance. METHODS AND MATERI...

Application value of gastric contrast ultrasonography in gastric tumors.

In recent years, gastric oral contrast ultrasonography (OCUS) and double contrast-enhanced ultrasonography (DCEUS) have emerged as promising imaging t...

A critical review of technical progress, clinical heterogeneity, and implementation challenges of artificial intelligence in digestive endoscopy.

INTRODUCTION: Digestive endoscopy is a critical modality for diagnosing and managing gastrointestinal diseases, yet it faces challenges including oper...

Recent advances in synthetic virtual 3D endoscopy to assist in skull base surgery.

INTRODUCTION: The advent of the operating microscope revolutionized neurosurgery by introducing stereoscopic visualization and enabling microneurosurg...

Study of bladder cancer detection in standard white light versus AI-supported endoscopy-01 (RAISE-01) - Development and validation of an AI-based support tool.

BACKGROUND: Diagnosis and surveillance of bladder cancer rely on white-light cystoscopy (WLC). However, this modality is operator-dependent and associ...

Identification of mitochondrial dynamics-related biomarkers in psoriasis using bioinformatics and Mendelian randomization.

Mitochondrial dynamics (MD) are crucial in various inflammatory disorders, yet the specific mechanisms involved in psoriasis remain inadequately under...

Detecting multimorbidity patterns in Alzheimer's disease using unsupervised machine learning: A nationwide emergency department study (2007-2022).

BackgroundAlzheimer's disease (AD) patients frequently present to emergency departments (EDs) with complex comorbidities that complicate triage and ma...

Multi-omics investigation of benzo[a]pyrene in gastric cancer: comprehensive network toxicology, machine learning and molecular docking approaches.

Gastric cancer (GC) risk is shaped by environmental exposures such as benzo[a]pyrene (BaP). Here, we systematically identified BaP-toxicological targe...

Molecular and immunological heterogeneity of eosinophilic esophagitis: Insights and subtyping.

BACKGROUND: Eosinophilic esophagitis (EoE) and its related subtypes-such as EoE-like esophagitis, lymphocytic esophagitis, and nonspecific esophagitis...

Machine learning and free energy clustering reveal PAH protein binding linked to AD risk.

This study develops a computational framework integrating bioinformatics, machine learning, and ΔG clustering to prioritize polycyclic aromatic hydroc...

Adherence to guidelines, pitfalls, and emerging technologies in endoscopic practice for celiac disease: a nationwide SIGENP survey.

UNLABELLED: Upper gastrointestinal endoscopy (UGIE) with duodenal biopsies remains the gold standard for diagnosing celiac disease (CD) in children an...

HIF3A-mediated aberrant activation of TXNIP promotes Alzheimer's disease progression.

Oxidative stress (OS) is a hallmark of Alzheimer's disease (AD), yet the cell type-specific mechanisms remain unclear. We analyzed a single-cell RNA s...

Automated Classification of Mitral and Tricuspid Regurgitation With Explainability and Real-World Practice Experience.

BACKGROUND: Mitral regurgitation and tricuspid regurgitation frequently coexist and are evaluated using overlapping echocardiographic views. Although ...

Future Perspectives for Artificial Intelligence in Allergy: Advances in Diagnosis, Monitoring, and Personalized Care.

Artificial intelligence (AI) is significantly transforming the specialty of allergy by offering novel tools for diagnosis, risk prediction, disease mo...

Effect of a Computer-Aided Device for Detecting Gastric Neoplasms: A Multicenter, Randomized Controlled Trial.

BACKGROUND & AIMS: Evidence about the effect of artificial intelligence (AI) on upper endoscopy in multicenter, randomized controlled trials is lackin...

Spatio-temporal characterization of gastric distensibility in upper endoscopy identifies the presence of Helicobacter pylori.

Assessment of gastric distensibility is crucial for understanding various gastrointestinal disorders, particularly those affecting gastric motility an...

Position Paper: IOlBD Evidence-based Consensus on the Use of Artificial Intelligence for Assessment of Endoscopic and Histologic Endpoints in Clinical Trials of Inflammatory Bowel Disease.

BACKGROUND & AIMS: Central reading of endoscopy and histopathology is the current standard for disease activity assessment in inflammatory bowel disea...

IMMT downregulation promotes osteoarthritis development by inducing mitochondrial dysfunction.

OBJECTIVE: This study aimed to identify key mitochondria-related genes involved in the pathogenesis of osteoarthritis (OA). METHODS: Publicly availabl...

Nitenpyram promotes breast cancer progression via PARP1: Integration of multi-omics analyses with experimental validation.

Nitenpyram (NIT) is an insecticide used primarily for flea control in pets, especially cats and dogs. Some studies suggest that NIT is associated with...