2019
DOI: 10.1002/hbm.24854
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Neuroimaging features of whole‐brain functional connectivity predict attack frequency of migraine

Abstract: Migraine is a chronic neurological disorder characterized by attacks of moderate or severe headache accompanying functionally and structurally maladaptive changes in brain. As the headache days/month is often measured by patient self-report and tends to be overestimated than actually experienced, the possibility of using neuroimaging data to predict migraine attack frequency is of great interest. To identify neuroimaging features that could objectively evaluate patients' headache days, a total of 179 migraineu… Show more

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Cited by 21 publications
(21 citation statements)
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References 35 publications
(49 reference statements)
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“…Further, a correlation analysis showed that the rsFC strength of the left amygdala with the left lingual gyrus was associated with headache frequency in migraineurs. This result supported previous findings that the migraine attack frequency could be predicted by fMRI-based machine learning approaches ( Mu et al, 2020 ; Tu et al, 2020 ). In clinical practice, the migraine attack frequency is often assessed by self-report, resulting in the measurement of headache frequency to become inaccurate and unreliable ( Berger et al, 2018 ; Haywood et al, 2018 ).…”
Section: Discussionsupporting
confidence: 92%
See 1 more Smart Citation
“…Further, a correlation analysis showed that the rsFC strength of the left amygdala with the left lingual gyrus was associated with headache frequency in migraineurs. This result supported previous findings that the migraine attack frequency could be predicted by fMRI-based machine learning approaches ( Mu et al, 2020 ; Tu et al, 2020 ). In clinical practice, the migraine attack frequency is often assessed by self-report, resulting in the measurement of headache frequency to become inaccurate and unreliable ( Berger et al, 2018 ; Haywood et al, 2018 ).…”
Section: Discussionsupporting
confidence: 92%
“…Because attack frequency is a risk factor for migraine progression, objective measurements are needed to accurately estimate migraine progression. Our results and previous finding ( Mu et al, 2020 ; Tu et al, 2020 ) suggested that neuroimaging markers might be used to predict factors for the estimation of migraine progression.…”
Section: Discussionsupporting
confidence: 83%
“…This approach has been taken in several published studies (2426). The classification accuracies for migraine, EM, and CM have ranged from about 65% to 95% depending on the study (2631). The most accurate models are those that classify individuals with more severe migraine burden (i.e.…”
Section: Brain Imaging: Structural and Functional Chronic Migraine Bimentioning
confidence: 99%
“…Machine learning (ML) provides a complementary strategy to guide individual-level prediction by integrating neuroimaging and clinical features. Although several recent studies used ML methods to investigate migraine-related features, such as classification, frequency, and the efficacy of acupuncture ( Chong et al, 2017 ; Mu et al, 2020 ; Yin et al, 2020 ), only a few studies used ML algorithms to predict the efficacy of NSAIDs in migraine.…”
Section: Introductionmentioning
confidence: 99%