Introduction to the Mining of Clinical Data

Clinics in Laboratory Medicine

Volumn 28, Issue 1, 2008, Pages 1-7

  Harrison Jr , James H ^a  

^a UNIVERSITY OF VIRGINIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLINICAL LABORATORY; CLINICAL STUDY; COMORBIDITY; DATA BASE; DATA MINING; DISEASE COURSE; ETHICS; GENE EXPRESSION; HEALTH CARE; INCIDENCE; LEGAL ASPECT; MEDICAL INFORMATICS; MEDICAL INFORMATION; MEDICAL RESEARCH; PHENOTYPE; PRIORITY JOURNAL; REVIEW; SOCIAL ASPECT;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; AUTOMATIC DATA PROCESSING; COMPUTATIONAL BIOLOGY; DATABASES, FACTUAL; HUMANS; INFORMATION STORAGE AND RETRIEVAL; MEDICAL RECORDS SYSTEMS, COMPUTERIZED; PATTERN RECOGNITION, AUTOMATED; TIME FACTORS;

EID: 37849046438     PISSN: 02722712     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cll.2007.10.001     Document Type: Review

References (21)

1. Rees J. Complex disease and the new clinical sciences. Science 296 (2002) 698-700
2. Canadian Institute for Health Research. Secondary use of personal information in health research: case studies. 2002. Available at: http://www.cihr-irsc.gc.ca/e/1475.html. Accessed August 26, 2007.
3. Safran C., Bloomrosen M., Hammond W.E., et al. Toward a national framework for the secondary use of health data: an American medical informatics association white paper. J Am Med Inform Assoc 14 1 (2007) 1-9
4. Grossman J., and Mackenzie F.J. The randomized controlled trial: gold standard, or merely standard?. Perspect Biol Med 48 4 (2005) 516-534
5. Jager K., Stel V., Wanner C., et al. The valuable contribution of observational studies to nephrology. Kidney Int 72 5 (2007) 539-542
6. Babcock C. Parallel processing mines retail data. Computerworld 28 39 (1994) 6
7. Harrison D. Backing up 100 terabytes. Network Computing 413 (1993) 98-104
8. Fayyad U.M., Piatetsky-Shapiro G., and Smyth P. From data mining to knowledge discovery: an overview. In: Fayyad U.M., Piatetsky-Shapiro G., and Smyth P. (Eds). Advances in knowledge discovery and data mining (1996), AAAI Press, Menlo Park (CA) 1-34
9. Lee S., and Siau K. A review of data mining techniques. Industrial Management & Data Systems 100 1 (2001) 41-46
10. Fayyad U.M., Piatetsky-Shapiro G., and Smyth P. From data mining to knowledge discovery in databases. AI Magazine 17 3 (1996) 37-54
11. Hipp J., Güntzer U., and Nakhaeizadeh G. Data mining of association rules and the process of knowledge discovery in databases. In: Perner P. (Ed). Advances in data mining: applications in e-commerce, medicine, and knowledge management (2002), Springer, Berlin (Germany) 207-226
12. Hand D.J. Principles of data mining. Drug Saf 30 7 (2007) 621-622
13. SAS Institute Inc. SAS Enterprise Miner®. Available at: http://www.sas.com/technologies/analytics/datamining/miner/index.html. Accessed August 26, 2007.
14. SPSS Inc. Clementine®. Available at: http://www.spss.com/clementine/. Accessed August 26, 2007.
15. Cognos Inc. Data mining. Available at: http://www.cognos.com/data-mining.html. Accessed August 26, 2007.
16. Insightful Corp. Insightful Miner®. Available at: http://www.insightful.com/products/iminer/default.asp. Accessed August 26, 2007.
17. Oracle Corp. Oracle data mining. Available at: http://www.oracle.com/technology/products/bi/odm/index.html. Accessed August 26, 2007.
18. Tan P., Steinbach M., and Kumar V. Introduction to data mining (2005), Addison-Wesley Longman Publishing Co., Inc., Boston
19. Dunham M.H. Data mining: introductory and advanced topics (2002), Prentice Hall, Upper Saddle River, NJ
20. Hand D., Blunt G., Kelly M., et al. Data mining for fun and profit. Stat Sci 15 2 (2000) 111-126
21. Cios K.J., and Moore G.W. Uniqueness of medical data mining. Artif Intell Med 26 1-2 (2002) 1-24