Novel methods for assessing fish blood biochemical data

Journal of Applied Ichthyology

Volumn 24, Issue 1, 2008, Pages 77-80

  Coz Rakovac, R ^a   Smuc, T ^a   Topic Popovic, N ^a   Strunjak Perovic, I ^a   Hacmanjek, M ^a   Jadan, M ^a  

^a RUDER BO KOVI INSTITUTE   (Croatia)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 38049113223     PISSN: 01758659     EISSN: 14390426     Source Type: Journal    
DOI: 10.1111/j.1439-0426.2007.01041.x     Document Type: Article

References (18)

1. Breiman, L., 2001 : Random forests. Mach. Learn. J. 45, 5 32.
2. Brown, L. A., 1993 : Anaesthesia and restraint. In : Fish medicine. M. K. Stoskopf Ed W.B. Saunders Co., Philadelphia, PA, USA, ISBN: 0-7216-2629-7. pp. 79 90.
3. Burtis, C. A. Ashwood, E. R., 2000 : Tietz fundamentals of clinical chemistry. W.B. Saunders, Philadelphia, PA, USA. 1091 pp.
4. Congleton, J. L. Wagner, T., 2006 : Blood-chemistry indicators of nutritional status and food intake in juvenile salmonids. J. Fish Biol. 69, 473 490.
5. Coz-Rakovac, R. Strunjak-Perovic, I. Hacmanjek, M. Topic Popovic, N. Lipej, Z. Sostaric, B., 2005 : Blood chemistry and histological properties of wild and cultured sea bass (Dicentrarchus labrax) in the North Adriatic. Vet. Res. Commun. 29, 677 687.
6. Delgado, M. J. Martinez-Alvarez, R. Pedro, N. de Guijarro, A. I. Lopez-Patino, M. A., 2005 : Daily and seasonal variations in haematological and blood biochemical parameters in the tench, Tinca tinca Linnaeus, 1758. Aquacult. Res. 36, 1185 1196.
7. Duda, R. O. Hart, P. E. Stork, D. G., 2000 : Pattern classification, Wiley-Interscience, New York, NY, USA, ISBN 0-471-05669-3. pp. 738.
8. Dzeroski, S. Drumm, D., 2003 : Using regression trees to identify the habitat preference of the sea cucumber (Holothuria leucospilota) on Rarotonga, Cook Islands. Ecol. Modell. 170, 219 226.
9. Edsall, C. C., 1999 : A blood chemistry profile for lake trout. J. Aquat. Anim. Health 11, 81 86.
10. Hrubec, T. C. Smith, S. A. Robertson, J. L., 2001 : Age related changes in haematology and plasma chemistry values of hybrid striped bass (Morone chysops; Morone saxatilis). Vet. Clin. Pathol. 30, 8 15.
11. Mastrorillo, S. Lek, S. Dauba, F. Belaud, A., 1997 : The use of artificial neural networks to predict the presence of small-bodied fish in a river. Freshw. Biol. 38, 237 246.
12. McQueen, R. J. Garner, S. R. Neveill-Manning, C. G. Whitten, I. H., 1995 : Applying machine learning to agricultural data. Comput. Electron. Agric. 12, 275 293.
13. Pickering, A. D. Pottinger, T. G. Christie, P., 1982 : Recovery of the brown trout, Salmo trutta L., from acute handling stress: a time-course study. J. Fish Biol. 20, 229 244.
14. Quinlan, J. R., 1992 : C4.5 Programs for machine learning. Morgan Kaufmann, San Mateo CA, USA, ISBN 1-55860-238-0, 240 pp.
15. Topic Popovic, N. Strunjak-Perovic, I. Coz-Rakovac, R. Hacmanjek, M. Jadan, M., 2006 : Comparison of five tuna plasma analytes measured on two automated blood analysers. Fish Physiol. Biochem. 32, 99 103.
16. Topic, G. Smuc, T. Sojat, Z. Skala, K., 2005 : Reimplementation of the random forest algorithm. In : Parallel Numerics 2005 (Theory and Applications), Portoroz, Slovenia. M. Vajtersic, R. Trobec, P. Zinterhof, A. Uhl (Eds JSI Publisher, Ljubljana, Salzburg, pp. 119 128.
17. Tschudi, P. R., 1995 : Evaluation of the dry chemical analyses system VetTest 8008. Schweiz. Arch. Tierheilkd. 137, 381 385.
18. Witten, I. H. Frank, E., 1999 : Data mining: practical machine learning tools and techniques with java implementations. Morgan Kaufmann, San Francisco, CA, USA, ISBN: 0-12-088407-0, 525 pp.