Minimal number of chicken daily growth velocities for artificial neural network detection of pulmonary hypertension syndrome (PHS)

Poultry Science

Volumn 80, Issue 3, 2001, Pages 254-259

  Roush, W B ^a   Wideman Jr , R F ^b   Cahaner, A ^c   Deeb, N ^c   Cravener, T L ^a  

^a PENNSYLVANIA STATE UNIVERSITY   (United States)

^b UNIVERSITY OF ARKANSAS   (United States)

^c HEBREW UNIVERSITY OF JERUSALEM   (Israel)

Author keywords

Artificial neural networks; Ascites; Broilers; Pulmonary hypertension

Indexed keywords

AGE; ANIMAL; ANIMAL DISEASE; ARTICLE; ARTIFICIAL NEURAL NETWORK; BIRD DISEASE; CHICKEN; DISEASE PREDISPOSITION; FEMALE; GROWTH, DEVELOPMENT AND AGING; IMMUNOLOGY; MALE; PULMONARY HYPERTENSION; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SYNDROME; TEMPERATURE; WEIGHT GAIN;

AGE FACTORS; ANIMALS; CHICKENS; DISEASE SUSCEPTIBILITY; FEMALE; HYPERTENSION, PULMONARY; MALE; NEURAL NETWORKS (COMPUTER); POULTRY DISEASES; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SYNDROME; TEMPERATURE; WEIGHT GAIN;

EID: 0035289676     PISSN: 00325791     EISSN: None     Source Type: Journal    
DOI: 10.1093/ps/80.3.254     Document Type: Article

References (13)

1. Masters, T., 1995. Advanced Algorithms for Neural Networks: A C++ Sourcebook. John Wiley & Sons, Inc., New York, NY.
2. National Research Council, 1994. Nutrient Requirements of Poultry. 9th rev. ed. National Academy Press, Washington, DC.
3. Roush, W. B., G. F. Barbato, and T. L. Cravener, 1994. A nonlinear dynamical (chaos) approach to the analysis of broiler growth. Poultry Sci. 73:1183-1195.
4. Roush, W. B., and T. L. Cravener, 1997. Artificial neural network prediction of amino acid levels in feed ingredients. Poultry Sci. 76:721-727.
5. Roush, W. B., T. L. Cravener, Y. Kochera-Kirby, and R. F. Wideman, Jr., 1997. Probabilistic neural network prediction of ascites in broilers based on minimally invasive physiological factors. Poultry Sci. 76:1513-1516.
6. Roush W. B., Y. Kochera-Kirby, T. L. Cravener, and R. F. Wideman, Jr., 1996. Artificial neural network prediction of ascites in broilers. Poultry Sci. 75:1479-1487.
7. Roush, W. B., and R. F. Wideman, Jr., 2000. Evaluation of broiler growth velocity and acceleration in relation to pulmonary hypertension syndrome (PHS). Poultry Sci. 79:180-191.
8. Skapura, D. M., 1996. Building Neural Networks. Addison-Wesley Publishing Company, Reading, MA.
9. Tsonis, P. A., and A. A. Tsonis, 1989. Chaos: Principles and implications in biology. CABIOS (Computer Applications in the Biosciences) 5:27-32.
10. Ward Systems Group, 1996. NeuroShell 2. Ward Systems Group, Inc. Frederick, MD.
11. Wideman, R. F., Jr., 2000. Cardio-pulmonary hemodynamics and ascites in broiler chickens. Avian Poult. Biol. Rev. 11:21-43.
12. Wideman, R. F., Jr., and H. French, 1999. Broiler breeder survivors of chronic unilateral pulmonary artery occlusion produce progeny resistant to pulmonary hypertension syndrome (ascites) induced by cool temperature. Poultry Sci. 78:404-411.
13. Wideman, R. F., Jr., and H. French, 2000. Ascites resistance of progeny from broiler breeder selected for two generations using chronic unilateral pulmonary artery occlusion. Poultry Sci. 79:396-401.