Pérez-Benito FJ, Conejero JA, Sáez C, et al. - Researchers sought to examine the critical features that allow differentiation of subgroups of patients with migraine according to the intensity and frequency of attacks. They used machine-learning algorithms for this study. Participants comprised 67 women with migraine. When the migraine intensity is considered, women with regular migraine headache intensity of 7 were noted to have following features: these were younger, had lower joint positioning sense error in cervical rotation, greater cervical mobility in rotation and flexion, lower flexion-rotation test, positive passive accessory intervertebral movements reproducing migraine, normal pressure pain thresholds over tibialis anterior, shorter migraine history, and lower cranio-vertebral angle in standing than the remaining migraine intensity subgroups. The flexion-rotation test to the symptomatic side was the most discriminative variable. Using the machine-learning algorithms, thus they recognized a subgroup of women with migraine with common migraine intensity.