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Panic Attack Prediction Using Wearable Devices and Machine Learning: Development and Cohort Study

Panic Attack Prediction Using Wearable Devices and Machine Learning: Development and Cohort Study

Liu et al [13] used 11 predictors for PD recurrence from past demographic, clinical, and psychosocial factors, yielding a discriminative power C statistic of 72.8%. Most clinical questionnaires can be delivered at clinics or via internet-based approaches. f MRI [14-17] compares areas of brain activation before and after a particular treatment, clarifies the structural change in PD, and predicts whether PD is comorbid with depression. However, predictions from different f MRI studies are inconsistent [18].

Chan-Hen Tsai, Pei-Chen Chen, Ding-Shan Liu, Ying-Ying Kuo, Tsung-Ting Hsieh, Dai-Lun Chiang, Feipei Lai, Chia-Tung Wu

JMIR Med Inform 2022;10(2):e33063