1. An artificial intelligence system for the analysis of nucleic acid microarray hybridization information related to an individual patient for diagnosing a physiological condition of said patient and for recommending treatment for said patient, comprising: (i) a user facility comprising a nucleic acid microarray having a surface comprising nucleic acid probes comprising about 25 to about 70 bases in length tethered to said microarray surface, and an optical scanning system configured to collect hybridization information from said microarray, said hybridization information comprising gene expression information related to said patient, said user facility being configured to provide gene expression information, (ii) a Web server that communicates with at least one user facility, configured to perform a group of functions comprising receiving and transmitting hybridization information related to said patient, supporting data analyses, and providing security and business functions, wherein said gene expression information related to said patient comprises hybridization information collected from said microarray contacted with a clinical sample related to said patient, (iii) a database server that is configured to perform a group of functions comprising storing hybridization profiles, clinical information associated with hybridization profiles, personal medical history information related to the patient, treatments suitable for diagnosed conditions related to hybridization profiles, data related information, and statistical information associated with hybridization profiles; and (iv) an application server that is configured to recognize a diagnostic master user corresponding to a user facility and a diagnostic user corresponding to an individual patient associated with said diagnostic master user, to facilitate information exchange between the Web server and the database server, to analyze said hybridization information through the use of a rate algorithm comprising detecting high gene expression levels, detecting low gene expression levels, and relating said gene expression levels with patient family history to determine a likelihood of developing a specific disease, and to perform a group of functions comprising: diagnosing a physiological condition of the patient suggested by the rate algorithm, and recommending methods of treatment for said patient based on the diagnosed physiological condition.