Uniqueness of medical data mining

This article addresses the special features of data mining with medical data. Researchers in other fields may not be aware of the particular constraints and difficulties of the privacy-sensitive, heterogeneous, but voluminous data of medicine. Ethical and legal aspects of medical data mining are discussed, including data ownership, fear of lawsuits, expected benefits, and special administrative issues. The mathematical understanding of estimation and hypothesis formation in medical data may be fundamentally different than those from other data collection activities. Medicine is primarily directed at patient-care activity, and only secondarily as a research resource; almost the only justification for collecting medical data is to benefit the individual patient. Finally, medical data have a special status based upon their applicability to all people; their urgency (including life-or-death); and a moral obligation to be used for beneficial purposes.

[1]  Latanya Sweeney,et al.  Computational disclosure control: a primer on data privacy protection , 2001 .

[2]  G W Moore,et al.  A prototype Internet autopsy database. 1625 consecutive fetal and neonatal autopsy facesheets spanning 20 years. , 1996, Archives of pathology & laboratory medicine.

[3]  G Hripcsak,et al.  Evaluating Natural Language Processors in the Clinical Domain , 1998, Methods of Information in Medicine.

[4]  C. M. Sperberg-McQueen,et al.  Extensible markup language , 1997 .

[5]  D. Lindberg,et al.  Unified Medical Language System , 2020, Definitions.

[6]  K. Cios Medical data mining and knowledge discovery. , 2000, IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society.

[7]  C K Osborne,et al.  Efficacy of adjuvant chemotherapy in high-risk node-negative breast cancer. An intergroup study. , 1989, The New England journal of medicine.

[8]  C. M. Sperberg-McQueen,et al.  eXtensible Markup Language (XML) 1.0 (Second Edition) , 2000 .

[9]  VYoshinori Yaginuma High-performance Data Mining System , 2001 .

[10]  C. Meinert,et al.  Effects of hypoglycemic agents on vascular complications in patients with adult-onset diabetes. IV. A preliminary report on phenoformin results. , 1971, JAMA.

[11]  Zdzislaw Pawlak,et al.  Rough classification , 1984, Int. J. Hum. Comput. Stud..

[12]  G W Moore,et al.  Maintaining patient confidentiality in the public domain Internet Autopsy Database (IAD). , 1996, Proceedings : a conference of the American Medical Informatics Association. AMIA Fall Symposium.

[13]  Roy Goldman,et al.  Lore: a database management system for semistructured data , 1997, SGMD.

[14]  K.J. Cios,et al.  Issues in automating cardiac SPECT diagnosis , 2000, IEEE Engineering in Medicine and Biology Magazine.

[15]  Gregory Piatetsky-Shapiro,et al.  Advances in Knowledge Discovery and Data Mining , 2004, Lecture Notes in Computer Science.

[16]  Jean-Pierre Changeux,et al.  Conversations on mind, matter, and mathematics , 1995 .

[17]  Lukasz A. Kurgan,et al.  Knowledge discovery approach to automated cardiac SPECT diagnosis , 2001, Artif. Intell. Medicine.

[18]  Matthias Baumgarten,et al.  Data mining and XML: current and future issues , 2000, Proceedings of the First International Conference on Web Information Systems Engineering.

[19]  Jürgen Dix,et al.  Nonmonotonic Reasoning: An Overview , 1997, CSLI Lecture Notes.

[20]  K.J. Cios,et al.  From the guest editor medical data mining and knowledge discovery , 2000, IEEE Engineering in Medicine and Biology Magazine.

[21]  염흥렬,et al.  [서평]「Applied Cryptography」 , 1997 .

[22]  Witold Pedrycz,et al.  Data Mining Methods for Knowledge Discovery , 1998, IEEE Trans. Neural Networks.

[23]  Bruce Schneier,et al.  Applied cryptography : protocols, algorithms, and source codein C , 1996 .

[24]  Jiawei Han,et al.  Mining MultiMedia Data , 1999 .

[25]  Rebecca Herold,et al.  Standards for privacy of individually identifiable health information. Office of the Assistant Secretary for Planning and Evaluation, DHHS. Final rule. , 2001, Federal register.

[26]  Eric Apps New data mining industry standards: moving from the monks to the mainstream , 2000 .

[27]  G. Knatterud,et al.  Effects of hypoglycemic agents on vascular complications in patients with adult-onset diabetes. 3. Clinical implications of UGDP results. , 1971, JAMA.

[28]  D. W. Barron Machine Translation , 1968, Nature.

[29]  Bruce Schneier,et al.  Applied cryptography (2nd ed.): protocols, algorithms, and source code in C , 1995 .

[30]  Delegations of authority and organization; Office of the Commissioner--FDA. Final rule. , 1991, Federal register.

[31]  Treatment and survival of patients with cancer of the prostate. The Veterans Administration Co-operative Urological Research Group. , 1967, Surgery, gynecology & obstetrics.

[32]  Forouzan Golshani,et al.  Proceedings of the Eighth International Conference on Data Engineering , 1992 .

[33]  Padhraic Smyth,et al.  Knowledge Discovery and Data Mining: Towards a Unifying Framework , 1996, KDD.

[34]  Xue Z. Wang,et al.  Data Mining and Knowledge Discovery — an Overview , 1999 .

[35]  Vijay K. Rohatgi,et al.  Advances in Fuzzy Set Theory and Applications , 1980 .

[36]  Lotfi A. Zadeh,et al.  Fuzzy sets and information granularity , 1996 .

[37]  Hinrich Schütze,et al.  Book Reviews: Foundations of Statistical Natural Language Processing , 1999, CL.

[38]  Werner Ceusters,et al.  Medical Natural Language Understanding as a Supporting Technology for Data Mining in Healthcare. , 2001 .

[39]  Vishu Krishnamurthy,et al.  Oracle8i-the XML enabled data management system , 2000, Proceedings of 16th International Conference on Data Engineering (Cat. No.00CB37073).

[40]  Josephine M. Cheng,et al.  XML and DB2 , 2000, Proceedings of 16th International Conference on Data Engineering (Cat. No.00CB37073).

[41]  Hhs Office for Civil Rights Standards for privacy of individually identifiable health information. Final rule. , 2002, Federal register.

[42]  C. M. Sperberg-McQueen,et al.  Extensible Markup Language (XML) , 1997, World Wide Web J..

[43]  H. Schoning Tamino - a DBMS designed for XML , 2001, Proceedings 17th International Conference on Data Engineering.

[44]  Barr and Feigenbaum Edward A. Avron The Handbook of Artificial Intelligence , 1981 .

[45]  Zhaohui Tang,et al.  Building Data Mining Solutions with SQL Server 2000 , 2000 .

[46]  G W Moore,et al.  Token swap test of significance for serial medical data bases. , 1986, The American journal of medicine.

[47]  Grover M. Hutchins,et al.  Effort and demand logic in medical decision making , 1980 .

[48]  Michael J. Pazzani,et al.  Knowledge discovery from data? , 2000, IEEE Intell. Syst..

[49]  M R Kosorok,et al.  Risk of persistent growth impairment after alternate-day prednisone treatment in children with cystic fibrosis. , 2000, The New England journal of medicine.

[50]  R Denis,et al.  [Survival of patients with cancer of the prostate]. , 1972, Journal d'urologie et de nephrologie.

[51]  K. Cios,et al.  A knowledge discovery approach to diagnosing myocardial perfusion , 2000, IEEE Engineering in Medicine and Biology Magazine.

[52]  Le Gruenwald,et al.  A survey of data mining and knowledge discovery software tools , 1999, SKDD.

[53]  Harald Schöning Tamino - A DBMS designed for XML , 2001, ICDE.