A Provenance Model Based on Declarative Specifications for Intensive Data Analyses in Hemotherapy Information Systems

Carregando...
Imagem de Miniatura
Citações na Scopus
Tipo de produção
conferenceObject
Data de publicação
2014
Título da Revista
ISSN da Revista
Título do Volume
Editora
IEEE
Autores
ALMEIDA, Fernanda Nascimento
TUNES, Gisela
FERREIRA, Joao Eduardo
Citação
2014 IEEE 10TH INTERNATIONAL CONFERENCE ON E-SCIENCE (E-SCIENCE), VOL 1, p.92-99, 2014
Projetos de Pesquisa
Unidades Organizacionais
Fascículo
Resumo
In the donation process, blood donors are screened for the level of hemoglobin or hematocrit in order to protect them from developing anemia. Nevertheless, there is no standard procedure to predict anemia development after blood donation. The Sao Paulo Blood Center is responsible for maintaining a database with information on each donation. However, this database doesn't have a good quality and consequently it is difficult to establish systematic analysis using the donation database without previous data validations. In order to provide a better quality of donation data, this paper presents a provenance description based on a classification criteria defined by specialists. More concretely, this paper answers the follow main question: is there a connection between blood donation and decrease in hematocrit level in order to prevent undesirable outcomes to blood donors? In this paper we show that it is possible to provide detailed investigations in order to answer this main question using the data description without the need to impose changes in the current database system structures that is sponsored by Sao Paulo Blood Center.
Palavras-chave
Referências
  1. Almeida F.N., 2010, 4 BRAZ E SCI WORKSH
  2. Altintas I, 2006, LECT NOTES COMPUT SC, V4145, P118
  3. ALVAREZ TL, 2006, IPAW, P28
  4. Bavoil L, 2005, IEEE Visualization 2005, Proceedings, P135
  5. Braga Juliana Cristina, 2008, IEEE Latin America Transactions, V6, P207, DOI 10.1109/TLA.2008.4609919
  6. Buneman P., 2001, INT C DAT THEOR 4 6, P15
  7. Buneman P., 2000, FDN SOFTWARE TECHNOL, P9
  8. Carneiro-Proietti AB, 2010, TRANSFUSION, V50, P918, DOI 10.1111/j.1537-2995.2009.02529.x
  9. Cavalcanti MC, 2005, DATA KNOWL ENG, V53, P45, DOI 10.1016/j.datak.2004.06.013
  10. Freire J, 2008, COMPUT SCI ENG, V10, P11, DOI 10.1109/MCSE.2008.79
  11. Gaudet P, 2012, DATABASE-OXFORD, DOI 10.1093/database/bas036
  12. GENTLEMAN R, 1994, BIOMETRIKA, V81, P618
  13. Goble C., 2005, SEMANT WEB, P355
  14. Gonçalez Thelma, 2003, Rev Panam Salud Publica, V13, P144, DOI 10.1590/S1020-49892003000200016
  15. Hosmer DW, 2008, APPL SURVIVAL ANAL R
  16. Ikeda R., 2010, B IEEE COMP SOC TECH
  17. Mendrone A, 2009, TRANSFUSION, V49, P662, DOI 10.1111/j.1537-2995.2008.02023.x
  18. Moreau L., 2007, COMMUN ACM, V4, P52
  19. Oinn T, 2006, CONCURR COMP-PRACT E, V18, P1067, DOI 10.1002/cpe.993
  20. Simmhan Y.L., 2005, TR618 IND U COMP SCI
  21. Stevens R, 2007, BRIEF BIOINFORM, V8, P183, DOI 10.1093/bib/bbm015
  22. Stevenson P, 2011, DATABASE-OXFORD, DOI 10.1093/database/bar029
  23. Wong N, 2005, IEEE IC CAD, P801, DOI 10.1109/ICCAD.2005.1560173
  24. Woodruff A, 1997, PROC INT CONF DATA, P91, DOI 10.1109/ICDE.1997.581742
  25. Yousefinejad Vahid, 2010, Asian J Transfus Sci, V4, P123, DOI 10.4103/0973-6247.67032