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Updated: Sep 9, 2025

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
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東アジアの人口における冬型季節性基準の最適化:季節性パターン評価アンケートを使用した機械学習アプローチ

Ji Won Yeom1,2, Jung-Been Lee3, Soohyun Park1,2

  • 1Department of Psychiatry, Korea University College of Medicine, Seoul, Republic of Korea.

Brain and behavior
|September 3, 2025
PubMed
まとめ

マシン・ラーニングは東アジアの人々の季節性情動障害 (SAD) の基準を改良しました. 新しい基準は,単に"最悪な気分"の月を超えて,追加の症状を考慮することによって,冬型のSADの識別を改善します.

キーワード:
東アジア季節的パターン評価アンケート (SPAQ)機械学習季節性感情障害 (SAD)冬型の季節性

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