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Comorbid insomnia among breast cancer survivors and its prediction using machine learning: a nationwide study in Japan.

Taro UenoDaisuke IchikawaYoichi ShimizuTomomi NarisawaKatsunori TsujiEisuke OchiNaomi SakuraiHiroji IwataYutaka J Matsuoka
Published in: Japanese journal of clinical oncology (2021)
The high prevalence of sleep problems and its link with mortality warrants routine screening. Our novel predictive model using a machine learning approach offers clinically important insights for the early detection of comorbid insomnia and intervention in breast cancer survivors.
Keyphrases
  • sleep quality
  • machine learning
  • randomized controlled trial
  • mental health
  • cardiovascular events
  • depressive symptoms
  • physical activity
  • clinical practice
  • risk factors
  • big data
  • cardiovascular disease