Call for papers

Artificial Intelligence in Medicine

Special Issue on
Data Mining Techniques and Applications in Medicine

Guest editors:
Blaz Zupan, Nada Lavrac, and Elpida Keravnou

• Background
• Objective
• Submission guidelines
• Guest editors (addresses)

• Take a flyer (letter, A4)

Background

With the widespread use of medical information systems that include databases which have recently featured explosive growth in their sizes, physicians and medical researchers are faced with a problem of making use of the stored data. The traditional manual data analysis has become insufficient, and methods for efficient computer-assisted analysis indispensable, in particular those of data mining and other related techniques of knowledge discovery in databases and intelligent data analysis.

Objective

This special issue will address current techniques and applications of data mining in medicine. While the general goal of applying data mining techniques in medicine is to directly or indirectly enhance the provision of health care, the specific goals are the extraction (discovery) of medical knowledge for diagnosis, screening, prognosis, monitoring, outcomes research, therapy support or overall patient management. Some of the topics relevant to this special issue on data mining (DM) in medicine are:

• DM techniques, particularly suited for medical applications.
• Criteria for selecting a particular DM technique or sets of techniques.
• Quality assessment measures for DM, e.g., validity, utility, comprehensibility, and novelty of discovered knowledge.
• Medical domains where DM was applied, providing a motivation for DM, describing data properties (e.g., existence of noise, non-homogeneous data, missing values) and availability of background knowledge.
• Inclusion of medical experts/physicians in the preparation of data for DM (e.g., data representation, modeling, cleaning, selection, and transformation), as well as in the interpretation of results.
• Issues related to the representation of extracted knowledge.
• Dissemination of results: How did the results of DM affect medical practice or how did they assist in medical research.
• The integration of DM tools into the existing medical information systems.
• How can your successful (unsuccessful?) application of DM methods be generalized: for which types of medical domains, which specific properties of data?
• What are the prospects of applying DM techniques in medicine? Lessons on how to increase the acceptance of these tools by physicians and medical experts.

Submission guidelines

All the manuscripts submitted will be subject to a rigorous review process. Submissions of full papers should be limited to at most 30 pages including figures, tables, and references. The text should be in 12pt font, 1.5 line-spacing (at most 15,000 words), leaving a 3 cm (1.2 inches) margin at each side. You may also use submission guidelines provided by the publisher. Papers must not have appeared in, nor be under consideration by other journals. Papers should start with a title page that includes title, authors and their affiliation, abstract of about 100 words, up to 5 keywords, and the information on the contact author (full address, phone and fax number, e-mail address).

To submitt a paper, please:

• Send 4 (four) copies of each submission to the address:

  Blaz Zupan
  Department of Intelligent Systems
  J. Stefan Institute
  Jamova 39
  SI-1000 Ljubljana
  Slovenia

  The paper should be received by 1st February 1998.

• E-mail the title page (title, authors and their affiliation, abstract of about 100 words, up to 5 keywords, and the information on the contact author necessary including e-mail address). Please use plain ASCII text format (no attachements). Send the e-mail to

  blaz.zupan@ijs.si

  by 1st February 1998. Please use the subject name "AIM TITLE first-author's-name" (like "AIM TITLE zupan").

• E-mail the complete paper in either PostScript or PDF format. For the e-mail, please use the subject name "AIM first-author's-name" (like "AIM zupan"). Send the e-mail to

  blaz.zupan@ijs.si

  by 1st February 1998.

Guest editors

Blaz Zupan and Nada Lavrac
Department of Intelligent Systems
J. Stefan Institute
Jamova 39
SI-1000 Ljubljana
Slovenia
phone: +386 61 177 3380, +386 61 177 3272
fax: +386 61 125 1038
e-mail: blaz.zupan@ijs.si, nada.lavrac@ijs.si

Elpida Keravnou
Department of Computer Science
University of Cyprus
75 Kallipoleos Street
P.O. Box 537
CY-1678
Nycosia
phone: +357 2 338 705
fax: +357 2 339 062
e-mail: elpida@turing.cs.ucy.ac.cy