title: Introduction to the mining of clinical data.
abstract: The increasing volume of medical data online, including laboratory data, represents a substantial resource that can provide a foundation for improved understanding of disease presentation, response to therapy, and health care delivery processes. Data mining supports these goals by providing a set of techniques designed to discover similarities and relationships between data elements in large data sets. Currently, medical data have several characteristics that increase the difficulty of applying these techniques, although there have been notable medical data mining successes. Future developments in integrated medical data repositories, standardized data representation, and guidelines for the appropriate research use of medical data will decrease the barriers to mining projects.
authors.affiliation: Division of Clinical Informatics, Department of Public Health Sciences, University of Virginia, Suite 3181 West Complex, 1335 Hospital Drive, Charlottesville, VA 22908-0717, USA. james.harrison@virginia.edu
authors.forename: James H
authors.initials: JH
authors.lastname: Harrison
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D019295:Computational Biology; D016208:Databases, Factual; D001330:Electronic Data Processing; D006801:Humans; D016247:Information Storage and Retrieval / Q000941:ethics / Q000331:legislation & jurisprudence; D016347:Medical Records Systems, Computerized / Q000941:ethics / Q000331:legislation & jurisprudence; D010363:Pattern Recognition, Automated; D013997:Time Factors