Purchase one-time access:
Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online accessOne-time access price info
- For academic or personal research use, select 'Academic and Personal'
- For corporate R&D use, select 'Corporate R&D Professionals'
Subscribers receive full online access to your subscription and archive of back issues up to and including 2002.
Content published before 2002 is available via pay-per-view purchase only.
Subscribe:
Subscribe to Clinics in Laboratory MedicineReferences
- Dimensions of time in illness: an objective view.Ann Intern Med. 2000; 132: 45-53
- Myocardial infarction redefined—a consensus document of The Joint European Society of Cardiology/American College of Cardiology Committee for the redefinition of myocardial infarction.J Am Coll Cardiol. 2000; 36: 959-969
- Natural history of chronic hepatitis B and C.J Gastroenterol Hepatol. 1999; 14: S1-S5
Wiederhold G, Fries JF. Structured organization of clinical data bases. Proceedings of the American Federation of Information Processing Societies National Computer Conference (AFIPS) 1975;44:479–85.
- Fundamentals of database systems.3rd edition. Addison-Wesley, New York2000
- Temporal reasoning in medicine.in: Fisher M. Gabbay D. Vila L. Handbook of temporal reasoning in artificial intelligence. Elsevier, New York2005: 587-653
- Etzion O. Jajodia S. Sripada S. Temporal databases: research and practice. Transitioning temporal support in TSQL2 to SQL3. vol. 1399. Springer, Berlin1998: 150-194
- Maintaining knowledge about temporal intervals.Commun ACM. 1983; 26: 832-843
- Temporal constraint networks.Artif Intell. 1991; 49: 61-95
- Temporal representation and reasoning in medicine: research directions and challenges.Artif Intell Med. 2006; 38: 101-113
- Clinical data retrieval: 25 years of temporal query management at the University of Vienna Medical School.Methods Inf Med. 2002; 41: 89-97
- Temporal expressiveness in querying a time-stamp–based clinical database.J Am Med Inform Assoc. 2000; 7: 152-163
- The Chronus II temporal database mediator.Proc AMIA Symp. 2002; : 567-571
- A knowledge-based time-oriented active database approach for intelligent abstraction, querying and continuous monitoring of clinical data.Medinfo. 2004; 11: 84-88
- RASTA: a distributed temporal abstraction system to facilitate knowledge-driven monitoring of clinical databases.Medinfo. 2001; 10: 508-512
- A framework for knowledge-based temporal abstraction.Artif Intell. 1997; 90: 79-133
- A survey of temporal knowledge discovery paradigms and methods.Knowledge and Data Engineering, IEEE Transactions on. 2002; 14: 750-767
- Exploratory medical knowledge discovery: experiences and issues.SIGKDD Explor. Newsl. 2003; 5: 94-99
Antunes CM, Oliveira AL. Temporal data mining: an overview. Paper presented at the Proceedings of the Knowledge Discovery and Data Mining Workshop on Temporal Data Mining (KDD 01); Aug 26–29, 2001. San Francisco.
- Preventing meaningless stock time series pattern discovery by changing perceptually important point detection.Fuzzy Systems and Knowledge Discovery. 2005; : 1171-1174
Keogh E, Lin J, Fu A. HOT SAX: finding the most unusual time series subsequence: algorithms and applications. Paper presented at the 5th IEEE International Conference on Data Mining. New Orleans (LA), November 27–30, 2005.
Keogh E, Pazzani M. An enhanced representation of time series which allows fast and accurate classification, clustering, and relevance feedback. AAAI Press; Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining. 1998. p. 239–41.
- Health information systems—past, present, future.Int J Med Inform. 2006; 75: 268-281
- Using linear regression functions to abstract high-frequency data in medicine.Proc AMIA Symp. 2000; : 492-496
- A novel method for the efficient retrieval of similar multiparameter physiologic time series using wavelet-based symbolic representations.AMIA Annu Symp Proc. 2006; : 679-683
- Information mining over heterogeneous and high-dimensional time-series data in clinical trials databases.IEEE Trans Inf Technol Biomed. 2006; 10: 254-263
Ratanamahatana CA, Keogh E. Everything you know about dynamic time warping is wrong. Paper presented at the Third Workshop on Mining Temporal and Sequential Data (KDD-2004). Seattle (WA), August 22–25, 2004.
- Recognition of critical situations from time series of laboratory results by case-based reasoning.J Am Med Inform Assoc. 2002; 9: 520-528
- Analysis of time series.4th edition. Chapman and Hall, New York1989
- Temporal abstractions for interpreting diabetic patients monitoring data.Intelligent Data Analysis. 1998; 2: 97-122
- An introduction to wavelets.IEEE Comput Sci Eng. 1995; 2: 50-61
- Detection of outbreaks from time series data using wavelet transform.Proc AMIA Symp. 2003; : 748-752
Keogh E, Lin J, Truppel W. Clustering of time series subsequences is meaningless: implications for previous and future research. Paper presented at The Third IEEE International Conference on Data Mining (ICDM '03). Melbourne (FL), November 19–22, 2003.
Hoppner F. Time series abstraction methods—a survey. Paper presented at the Dortmund, Germany: GI Jahrestagung; September 30–Oct 3; 2002.
- Learning dependencies in multivariate time series. Paper presented at the ECAI'02 Workshop on Knowledge Discovery in (Spatio-) Temporal Data.Lyon, FranceJuly 22–23, 2002
- Temporal data mining for the quality assessment of hemodialysis services.Artif Intell Med. 2005; 34: 25-39
- Temporal abstraction in intelligent clinical data analysis: a survey.Artif Intell Med. 2007; 39: 1-24
- Semi-automated entry of clinical temporal-abstraction knowledge.J Am Med Inform Assoc. 1999; 6: 494-511
- M-HTP: a system for monitoring heart transplant patients.Artif Intell Med. 1992; 4: 111-126
- Knowledge reuse: temporal-abstraction mechanisms for the assessment of children's growth.Proc Annu Symp Comput Appl Med Care. 1993; : 449-453
- Hypothesis-driven data abstraction with trend templates.Proc Annu Symp Comput Appl Med Care. 1993; : 444-448
- PROTEMPA: a method for specifying and identifying temporal sequences in retrospective data for patient selection.J Am Med Inform Assoc. 2007; 14: 674-683
Agrawal R, Srikant R. Fast algorithms for mining association rules in large databases. Paper presented at the 20th Int Conf Very Large Databases. Santiago de Chile, Chile: VLDB; September 12–15. 1994. Santiago de Chile, Chile.
Morchen F, Ultsch A. Discovering temporal knowledge in multivariate time series. Paper presented at the Gesellschaft fur Klassifikation (GfKI). Dortmund, Germany; March 9–11, 2004.
Morchen F. A better tool than Allen's relations for expressing temporal knowledge in interval data. Paper presented at the Theory and Practice of Temporal Data Mining (TPTDM 2006). Philadelphia; August 20–23, 2006.
- Information storage and retrieval.Wiley, New York1997
- Locating previously unknown patterns in data-mining results: a dual data- and knowledge-mining method.BMC Med Inform Decis Mak. 2006; 6: 13
- Pattern discovery on Australian medical claims data—a systematic approach.IEEE Trans Know Data Eng. 2005; 17: 1420-1435
McCallum A, Nigam K, Ungar LH. Efficient clustering of high-dimensional data sets with application to reference matching. Paper presented at the Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; Boston, MA: August 20–23, 2000.
- The HELLP syndrome (hemolysis, elevated liver enzymes, and low platelets): much ado about nothing?.Am J Obstet Gynecol. 1990; 162: 311-316
- Dexamethasone to improve maternal outcome in women with hemolysis, elevated liver enzymes, and low platelets syndrome.Am J Obstet Gynecol. 2005; 193: 1587-1590
- Dexamethasone treatment does not improve the outcome of women with HELLP syndrome: a double-blind, placebo-controlled, randomized clinical trial.Am J Obstet Gynecol. 2005; 193: 1591-1598
