Integrating Clinician Intelligence for Dementia Risk Prediction in Patients
with Mild Cognitive Impairment 
   Lead Investigator:    Meng Wang
   Institution      :    University of Calgary
   E-Mail           :    meng.wang1@ucalgary.ca
   Proposal ID      :    1510



   Proposal Description:
   Research Questions:  Does the integration of clinician beliefs improve the  accuracy of dementia risk prediction over conventional risk scores derived from  data alone for patients with MCI using the Bayesian approach?                     The objectives of this study are to:                                             1.      develop and validate clinically useful risk scores to predict dementia risk   in individuals with MCI                                                           2.      elicit and quantify clinician expert knowledge about prognostic risk factors  for 3-year dementia risk from MCI through SEE                                     3.      integrate data driven risk scores with elicited expert knowledge to predict   dementia risks over time for patients with MCI                                   Expected Outcomes:                                                               The deliverables of this research will include a web-based prognostic tool that  integrates clinician judgement and patient data for dementia risk assessment     for MCI subjects.  The goal is to develop a clinical decision support tool that  can provide more accurate and personalized risk estimates, inform risk           reduction strategies, supplement decision making, and reduce the negative         impact of dementia.