title: Artificial neural network modeling using clinical and knowledge independent variables predicts salt intake reduction behavior.
abstract: BACKGROUND
  High dietary salt intake is directly linked to hypertension and cardiovascular diseases (CVDs). Predicting behaviors regarding salt intake habits is vital to guide interventions and increase their effectiveness. We aim to compare the accuracy of an artificial neural network (ANN) based tool that predicts behavior from key knowledge questions along with clinical data in a high cardiovascular risk cohort relative to the least square models (LSM) method.
  
  
  METHODS
  We collected knowledge, attitude and behavior data on 115 patients. A behavior score was calculated to classify patients' behavior towards reducing salt intake. Accuracy comparison between ANN and regression analysis was calculated using the bootstrap technique with 200 iterations.
  
  
  RESULTS
  Starting from a 69-item questionnaire, a reduced model was developed and included eight knowledge items found to result in the highest accuracy of 62% CI (58-67%). The best prediction accuracy in the full and reduced models was attained by ANN at 66% and 62%, respectively, compared to full and reduced LSM at 40% and 34%, respectively. The average relative increase in accuracy over all in the full and reduced models is 82% and 102%, respectively.
  
  
  CONCLUSIONS
  Using ANN modeling, we can predict salt reduction behaviors with 66% accuracy. The statistical model has been implemented in an online calculator and can be used in clinics to estimate the patient's behavior. This will help implementation in future research to further prove clinical utility of this tool to guide therapeutic salt reduction interventions in high cardiovascular risk individuals.
authors.affiliation: 1 Division of Cardiology, Department of Internal Medicine, American University of Beirut, Beirut, Lebanon ; 2 Vascular Medicine Program, American University of Beirut Medical Center, Beirut, Lebanon ; 3 Department of Cardiovascular Medicine, Cleveland Clinic Foundation, Cleveland, Ohio, USA ; 4 Department of Electrical & Computer Engineering, 5 Department of Nutrition & Food Sciences, American University of Beirut, Beirut, Lebanon.
authors.forename: Hussain A
authors.initials: HA
authors.lastname: Isma'eel
authors.affiliation: 1 Division of Cardiology, Department of Internal Medicine, American University of Beirut, Beirut, Lebanon ; 2 Vascular Medicine Program, American University of Beirut Medical Center, Beirut, Lebanon ; 3 Department of Cardiovascular Medicine, Cleveland Clinic Foundation, Cleveland, Ohio, USA ; 4 Department of Electrical & Computer Engineering, 5 Department of Nutrition & Food Sciences, American University of Beirut, Beirut, Lebanon.
authors.forename: George E
authors.initials: GE
authors.lastname: Sakr
authors.affiliation: 1 Division of Cardiology, Department of Internal Medicine, American University of Beirut, Beirut, Lebanon ; 2 Vascular Medicine Program, American University of Beirut Medical Center, Beirut, Lebanon ; 3 Department of Cardiovascular Medicine, Cleveland Clinic Foundation, Cleveland, Ohio, USA ; 4 Department of Electrical & Computer Engineering, 5 Department of Nutrition & Food Sciences, American University of Beirut, Beirut, Lebanon.
authors.forename: Mohamad M
authors.initials: MM
authors.lastname: Almedawar
authors.affiliation: 1 Division of Cardiology, Department of Internal Medicine, American University of Beirut, Beirut, Lebanon ; 2 Vascular Medicine Program, American University of Beirut Medical Center, Beirut, Lebanon ; 3 Department of Cardiovascular Medicine, Cleveland Clinic Foundation, Cleveland, Ohio, USA ; 4 Department of Electrical & Computer Engineering, 5 Department of Nutrition & Food Sciences, American University of Beirut, Beirut, Lebanon.
authors.forename: Jihan
authors.initials: J
authors.lastname: Fathallah
authors.affiliation: 1 Division of Cardiology, Department of Internal Medicine, American University of Beirut, Beirut, Lebanon ; 2 Vascular Medicine Program, American University of Beirut Medical Center, Beirut, Lebanon ; 3 Department of Cardiovascular Medicine, Cleveland Clinic Foundation, Cleveland, Ohio, USA ; 4 Department of Electrical & Computer Engineering, 5 Department of Nutrition & Food Sciences, American University of Beirut, Beirut, Lebanon.
authors.forename: Torkom
authors.initials: T
authors.lastname: Garabedian
authors.affiliation: 1 Division of Cardiology, Department of Internal Medicine, American University of Beirut, Beirut, Lebanon ; 2 Vascular Medicine Program, American University of Beirut Medical Center, Beirut, Lebanon ; 3 Department of Cardiovascular Medicine, Cleveland Clinic Foundation, Cleveland, Ohio, USA ; 4 Department of Electrical & Computer Engineering, 5 Department of Nutrition & Food Sciences, American University of Beirut, Beirut, Lebanon.
authors.forename: Savo Bou Zein
authors.initials: SB
authors.lastname: Eddine
authors.affiliation: 1 Division of Cardiology, Department of Internal Medicine, American University of Beirut, Beirut, Lebanon ; 2 Vascular Medicine Program, American University of Beirut Medical Center, Beirut, Lebanon ; 3 Department of Cardiovascular Medicine, Cleveland Clinic Foundation, Cleveland, Ohio, USA ; 4 Department of Electrical & Computer Engineering, 5 Department of Nutrition & Food Sciences, American University of Beirut, Beirut, Lebanon.
authors.forename: Lara
authors.initials: L
authors.lastname: Nasreddine
authors.affiliation: 1 Division of Cardiology, Department of Internal Medicine, American University of Beirut, Beirut, Lebanon ; 2 Vascular Medicine Program, American University of Beirut Medical Center, Beirut, Lebanon ; 3 Department of Cardiovascular Medicine, Cleveland Clinic Foundation, Cleveland, Ohio, USA ; 4 Department of Electrical & Computer Engineering, 5 Department of Nutrition & Food Sciences, American University of Beirut, Beirut, Lebanon.
authors.forename: Imad H
authors.initials: IH
authors.lastname: Elhajj
keywords: Sodium chloride; artificial neural networks (ANNs); behavior prediction; dietary; dietary intervention; salt intake reduction