Personalized prediction of optimal water intake in adult population by blended use of machine learning and clinical data

HIGHLIGHTS

• who: Alberto Dolci from the Department University of have published the article: Personalized prediction of optimal water intake in adult population by blended use of machine learning and clinical data, in the Journal: Scientific Reports Scientific Reports
• what: The authors generated a ML algorithm which in combination with an optimization algorithm provides personalized advice for daily water intake to achieve optimal hydration, as defined by a target 24 h U u00ad Osm of 500 mOsm/kg in healthy adults.
• how: Once the most relevant features were identified in the dataset several ML methods . . .
  

   

  

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