1. A lung cancer screening system comprising: a database including patient population information in a structured format and for a patient population associated with lung cancer and a domain knowledge base including knowledge information about lung cancer; an individual patient record of an individual patient; and a processor configured, using a diagnosis module program tangibly embodied on a program storage device, to screen the individual patient record for a diagnosis of malignant lung cancer, the diagnosis screening comprising determining a current state of the individual patient from a combination of values from multiple variables of the individual patient and determining whether or not the current state of the individual patient indicates the diagnosis of the malignant lung cancer as a function of the individual patient record, the patient population information in the structured format, and the knowledge information about lung cancer from the domain knowledge base of the database, the processor configured to determine a probability less than 100 percent of the diagnosis that the patient is of the current state, the probability being a function of the individual patient record and the knowledge information about lung cancer; wherein the processor is configured to, for a first one of the values of a first one of the variables, receive different possible values from different sources for the first value of the individual patient, identify a conflict between the different sources, reconcile the conflict between the different possible values for the first value based on a knowledge base, the probability being a function of the reconciled conflict between the different possible values; wherein the processor further comprises a modeling module for extracting only patient records from the patient population information for patients with similar characteristics as the individual patient, and for analyzing the extracted patient population information of the database to determine a trend in the patients of the patient population with the similar characteristics of the individual patient as determined by the individual patient record, the modeling module predicting a progression of lung cancer in the patient based on the determined trend and predicting lung cancer risk.