Migraines

Altered aminoacid and lipid metabolism in a rat orofacial inflammation model determined by omics approach: potential role in trigeminal sensitisation.

BACKGROUND: Trigeminal activation and sensitisation involved in chronic inflammatory orofacial pain share several similarities with headaches, including migraine. Therefore, understanding the pathophysiological mechanisms is important to determine novel therapies, in which animal models are crucial. Here we aimed to identify key mediators, mechanisms and networks using unbiased multi-omic approach...

Unveiling new insights into migraine risk stratification using machine learning models of adjustable risk factors.

BACKGROUND: Migraine ranks as the second-leading cause of global neurological disability, affecting approximately 1.1 billion individuals worldwide with severe quality-of-life impairments. Although adjustable risk factors-including environmental exposures, sleep disturbances, and dietary patterns-are increasingly implicated in pathogenesis of migraine, their causal roles remain insufficiently char...

Diagnosing migraine from genome-wide genotype data: a machine learning analysis.

Migraine has an assumed polygenic basis, but the genetic risk variants identified in genome-wide association studies only explain a proportion of the ...

A novel intelligent grade classification architecture for Patent Foramen Ovale by Contrast Transthoracic Echocardiography based on deep learning.

Patent foramen ovale (PFO) is one of the main causes of ischemic stroke. Due to the complex characteristics of contrast transthoracic echocardiography...

Prediction of new-onset migraine using clinical-genotypic data from the HUNT Study: a machine learning analysis.

BACKGROUND: Migraine is associated with a range of symptoms and comorbid disorders and has a strong genetic basis, but the currently identified risk l...

Febrile neutropenia management in high-risk neutropenic patients: a narrative review on antibiotic prophylaxis and empirical treatment.

INTRODUCTION: Although febrile neutropenia (FN) remains a major cause of morbidity and mortality in patients with hematologic malignancies and hematop...

Artificial neural networks applied to somatosensory evoked potentials for migraine classification.

BACKGROUND: Finding a biomarker to diagnose migraine remains a significant challenge in the headache field. Migraine patients exhibit dynamic and recu...

Influence pathways of noise exposure on people's negative emotions and health across different activity contexts: A neural network-based double machine learning approach.

Noise is a major global environmental issue that raises concerns about both mental and physical health. However, few studies have investigated the med...

Systematic review of infodemiology studies using artificial intelligence: social media posts on HIV preexposure prophylaxis.

OBJECTIVES: To explore how artificial intelligence (AI) can enhance infodemiology, which distributes and scans information in the electronic medium, t...

Development of an artificial intelligence-enhanced warfarin interaction checker platform.

Warfarin is a common anticoagulant drug for thrombo-prophylaxis in stroke and venous thromboembolism, which has many advantages but also some disadvan...

Machine learning-based prediction of vesicoureteral reflux outcomes in infants under antibiotic prophylaxis.

We aimed to investigate the independent outcome predictors of continuous antibiotic prophylaxis (CAP) in vesicoureteral reflux, train a model to predi...

Machine learning models and classification algorithms in the diagnosis of vestibular migraine: A systematic review and meta-analysis.

OBJECTIVES: To perform a systematic review and meta-analysis to evaluate the effectiveness of machine learning (ML) algorithms in the diagnosis of ves...

Construction and validation of a predictive model for meningoencephalitis in pediatric scrub typhus based on machine learning algorithms.

To retrospectively analyze the clinical characteristics of pediatric scrub typhus (ST) with meningoencephalitis (STME) and to construct and validate p...

Artificial Intelligence and Predictive Modeling in the Management and Treatment of Episodic Migraine.

PURPOSE OF REVIEW: Artificial intelligence (AI) has impacted different aspects of headache medicine, from history taking and diagnosis to drug develop...

Prediction models for treatment response in migraine: a systematic review and meta-analysis.

BACKGROUND: Migraine is a complex neurological disorder with significant clinical variability, posing challenges for effective management. Multiple tr...

Functional Disability and Psychological Impact in Headache Patients: A Comparative Study Using Conventional Statistics and Machine Learning Analysis.

: Recent research has focused on exploring the relationships between various factors associated with headaches and understanding their impact on indiv...

Machine learning-driven identification of critical gene programs and key transcription factors in migraine.

BACKGROUND: Migraine is a complex neurological disorder characterized by recurrent episodes of severe headaches. Although genetic factors have been im...

A robust multimodal brain MRI-based diagnostic model for migraine: validation across different migraine phases and longitudinal follow-up data.

Inter-individual variability in symptoms and the dynamic nature of brain pathophysiology present significant challenges in constructing a robust diagn...

Influence of next-generation artificial intelligence on headache research, diagnosis and treatment: the junior editorial board members' vision - part 2.

Part 2 explores the transformative potential of artificial intelligence (AI) in addressing the complexities of headache disorders through innovative a...

Healthy core: Harmonizing brain MRI for supporting multicenter migraine classification studies.

Multicenter and multi-scanner imaging studies may be necessary to ensure sufficiently large sample sizes for developing accurate predictive models. Ho...