AIMC Topic: Migraine Disorders

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

The journal of headache and pain
BACKGROUND: Finding a biomarker to diagnose migraine remains a significant challenge in the headache field. Migraine patients exhibit dynamic and recurrent alterations in the brainstem-thalamo-cortical loop, including reduced thalamocortical activity...

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

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

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

Current pain and headache reports
PURPOSE OF REVIEW: Artificial intelligence (AI) has impacted different aspects of headache medicine, from history taking and diagnosis to drug development. AI has been shown to have predictive modeling in helping diagnose migraine and assist with pat...

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

The journal of headache and pain
BACKGROUND: Migraine is a complex neurological disorder with significant clinical variability, posing challenges for effective management. Multiple treatments are available for migraine, but individual responses vary widely, making accurate predictio...

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

The journal of headache and pain
BACKGROUND: Migraine is a complex neurological disorder characterized by recurrent episodes of severe headaches. Although genetic factors have been implicated, the precise molecular mechanisms, particularly gene expression patterns in migraine-associ...

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

The journal of headache and pain
Inter-individual variability in symptoms and the dynamic nature of brain pathophysiology present significant challenges in constructing a robust diagnostic model for migraine. In this study, we aimed to integrate different types of magnetic resonance...

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

PloS one
Multicenter and multi-scanner imaging studies may be necessary to ensure sufficiently large sample sizes for developing accurate predictive models. However, multicenter studies, incorporating varying research participant characteristics, MRI scanners...

Machine learning classification meets migraine: recommendations for study evaluation.

The journal of headache and pain
The integration of machine learning (ML) classification techniques into migraine research has offered new insights into the pathophysiology and classification of migraine types and subtypes. However, inconsistencies in study design, lack of methodolo...

Crowdsourcing Adverse Events Associated With Monoclonal Antibodies Targeting Calcitonin Gene-Related Peptide Signaling for Migraine Prevention: Natural Language Processing Analysis of Social Media.

JMIR formative research
BACKGROUND: Clinical trials demonstrate the efficacy and tolerability of medications targeting calcitonin gene-related peptide (CGRP) signaling for migraine prevention. However, these trials may not accurately reflect the real-world experiences of mo...