title: Intelligent system and risk of different diseases in the general population.
abstract: This is a new approach to define the risk of the general population for a specific disease. We use Bayesian theory to define the risk of the population. Analyzing the major risk factors of a disease, how they affect the incidence and/or prevalence of the disease, and the statistics of each risk factor in the population, along with the power of the Bayes theorem helps us define the risk of that population for that disease. To find out what the risk of the general population for a disease is, prospective epidemiological studies in the population shown are needed. These studies usually lead to the identification of the major risk factors for a disease and their impacts which are quite costly and requires a long time to get to the results. Also a large personnel is needed to perform effectively in the study. The result of the risk of the general population for a first heart attack using our software is in agreement with the result of the Framingham heart study. Large studies like Framingham is not available for other diseases to enable us to evaluate the accuracy of our software precisely. To overcome this shortage we have sought medical experts' evaluation of the predicted risk of the general population for other disease by this software, which needs to be completed.
authors.forename: N
authors.initials: N
authors.lastname: Zarrin-Khameh
authors.forename: A
authors.initials: A
authors.lastname: Barzi
authors.forename: S
authors.initials: S
authors.lastname: Sadeghi
mesh_terms: D001185:Artificial Intelligence; D005103:Expert Systems; D006801:Humans; D009203:Myocardial Infarction / Q000453:epidemiology; D011159:Population Surveillance; D012306:Risk; D012984:Software