Information Technology Reference
In-Depth Information
information about RDs. Two directions of future investigations for RDs recognition
can be outlined here: rare event simulation [21] and class imbalance problems [10].
The obtained results would facilitate the optimisation of RDs management in
children and adolescents, particularly in terms of a substantial improve in the diag-
nostics and treatment. Application of fuzzy logic approaches provide a significant
input in clinical medicine and particularly in pediatrics. In our opinion, it would be
quite useful for further perfection of the children and adolescent health care system
improvement.
The following categories of population should be considered as the beneficiaries
of this research: up to 5-6% of children population, who might have some RD, their
family members and care-givers. From the scientific point of view, the creation of
the management algorithms based on new approaches as well as the receipt of new
evidence in the area of the public health care, in particular, for resolving the RDs
related problems, would be a great novelty. The obtained materials could be used
as a database for health care management, for conducting a pre-marketing research
and clinical trials by pharmaceutical companies in order to establish the efficiency
of some medicines.
Acknowledgement.
This work was supported by Science and Technology Center in Ukraine
and Sh. Rustaveli National Foundation, Grant STCU-GNSF #5015; Sh. Rustaveli National
Foundation and Ministry of Education and Science of Georgia, Grant GNSF/ST08/6-460,
References
1. Acampora, G., Kiseliova, T., Pagava, K., Vitiello, A.: Towards Application of FML in
Suspicion of Non-Common Diseases. In: 2011 IEEE International Conference on Fuzzy
Systems, Taipei, Taiwan, pp. 2073-2079 (2011)
2. Acampora, G., Loia, V.: Fuzzy Control Interoperability and Scalability for Adaptive
Domotic Framework. IEEE Transactions on Industrial Informatics 1(2), 97-111 (2005)
3. Acampora, G., Loia, V., Vitiello, A.: Enhancing Transparent Fuzzy Controllers through
Temporal Concepts: An Application to Computer Games. In: 2010 International Con-
ference on Technologies and Applications of Artificial Intelligence, pp. 405-412 (2010)
4. Adlassnig, K.-P., Kolarz, G.: CADIAG-II: Computer-assisted Medical Diagnosis using
Fuzzy Subsets. In: Gupta, M.M., Sanchez, E. (eds.) Approximate Reasoning in Decision
Analysis, pp. 495-505. North Holland Publishing Company (1982)
5. Children's r.a.r.e disease network,
http://www.crdnetwork.org/
6. de la Paz, M.P., Groft, S.C. (eds.): Rare Diseases Epidemiology. Springer (2010)
7. Grzymala-Busse, J.W.: Managing Uncertainty in Expert Systems. The Kluwer Inter-
national Series in Engineering and Computer Science. Kluwer Academic Publishers,
Boston (1991)
8. Daniel, M., Hájek, P., Nguyen, H.P.: CADIAG-2 and MYCIN-like systems. Artificial
Intelligence in Medicine 9, 241-259 (1997)
