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Machine‐learning classification of bipolar disorder incorporating wearable‐derived core body temperature and actigraphy‐derived sleep indices

Abstract Aim This study aimed to classify patients with bipolar disorder (BD) and normal controls (NCs) using machine‐learning models that incorporate wearable‐derived core body temperature (CBT) and actigraphy‐derived sleep indices. Methods We enrolled 23 euthymic patients with BD and 43 NCs. Sleep...

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Principais autores: Kazuhiro Kurihara, Ayano Shiroma, Masaki Kamata, Naruyo Yoshimoto, Ayano Saso, Akiyoshi Shimura, Yukiko Imai, Tadashi Miyahara, Yoshikazu Takaesu
Formato: Artigo
Idioma:Inglês
Publicado em: Wiley 2026-06-01
coleção:PCN Reports
Assuntos:
actigraphy
bipolar disorder
circadian rhythm
core body temperature
phase angle difference
Acesso em linha:https://doi.org/10.1002/pcn5.70359
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