Cardiovascular disease incidence prediction by machine learning and statistical techniques: a 16-year cohort study from eastern mediterranean region

HIGHLIGHTS

• who: Kamran Mehrabani-Zeinabad from the (UNIVERSITY) have published the research: Cardiovascular disease incidence prediction by machine learning and statistical techniques: a 16-year cohort study from eastern Mediterranean region, in the Journal: (JOURNAL)
• what: In this study, the most contributing variables for CVD prediction were identified as age, SBP, FBS, two-hour postprandial glucose, diabetes_mellitus, history of heart disease, history of high blood pressure, and history of diabetes.
• how: This study confirmed that building a prediction model for CVD in each is valuable for screening and primary prevention strategies in that specific . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or E-mail:

  If you don't have an account, you can create one here.