@article {994,
	title = {Increased MRI-based Brain Age in chronic migraine patients},
	journal = {The Journal of Headache and Pain},
	volume = {24},
	year = {2023},
	pages = {133},
	abstract = {<p>Neuroimaging has revealed that migraine is linked to alterations in both the structure and function of the brain. However, the relationship of these changes with aging has not been studied in detail. Here we employ the Brain Age framework to analyze migraine, by building a machine-learning model that predicts age from neuroimaging data. We hypothesize that migraine patients will exhibit an increased Brain Age Gap (the difference between the predicted age and the chronological age) compared to healthy participants.</p>
},
	keywords = {Biomarkers, Brain age, machine learning, migraine disorders, neuroimaging},
	issn = {1129-2377},
	doi = {10.1186/s10194-023-01670-6},
	url = {https://doi.org/10.1186/s10194-023-01670-6},
	author = {Navarro-Gonz{\'a}lez, Rafael and Garc{\'\i}a-Azor{\'\i}n, David and Guerrero-Peral, {\'A}ngel L. and {\'A}lvaro Planchuelo-G{\'o}mez and Aja-Fern{\'a}ndez, Santiago and de Luis-Garc{\'\i}a, Rodrigo}
}
