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A

Gonçalves, H., Henriques-Coelho, T., Bernardes, J., Rocha, A. P., Brandão-Nogueira, A., & Leite-Moreira, A. (2010). Analysis of heart rate variability in a rat model of induced pulmonary hypertension. Medical Engineering and PhysicsMed. Eng. Phys., 32(7), 746 - 752.

Mendonça, A. M., Cardoso, F., Sousa, A. V., & Campilho, A. (2012). Automatic localization of the optic disc in retinal images based on the entropy of vascular directions. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)Lect. Notes Comput. Sci. (Vol. 7325 LNCS, pp. 424 - 431).

C

Goya-Esteban, R., De Sá, J. P. M., Rojo-Álvarez, J. L., & Barquero-Pérez, O. (2008). Characterization of heart rate variability loss with aging and heart failure using sample entropy. In Computers in CardiologyComput Cardiol (Vol. 35, pp. 41 - 44).

Costa-Santos, C., Bernardes, J., Antunes, L., & Ayres-de-Campos, D. (2011). Complexity and categorical analysis may improve the interpretation of agreement studies using continuous variables. Journal of Evaluation in Clinical PracticeJ. Eval. Clin. Pract., 17(3), 511 - 514.

D

Silva, L. M., Marques de Sá, J., & Alexandre, L. A. (2008). Data classification with multilayer perceptrons using a generalized error function. Neural NetworksNeural Netw., 21(9), 1302 - 1310.

De Sá, J. P. M., Gama, J., Sebastião, R., & Alexandre, L. A. (2009). Decision trees using the minimum Entropy-of-error principle. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)Lect. Notes Comput. Sci. (Vol. 5702 LNCS, pp. 799 - 807).

E

Silva, L. M., Felgueiras, C. S., Alexandre, L. A., & Marques de Sá, J. (2006). Error entropy in classification problems: A univariate data analysis. Neural ComputationNeural Comp., 18(9), 2036 - 2061.

Alexandre, L. A., & Marques De Sá, J. P. (2006). Error entropy minimization for LSTM training. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)Lect. Notes Comput. Sci. (Vol. 4131 LNCS - I, pp. 244 - 253).

Gonçalves, H., Pinto, P., Ayres-de-Campos, D., & Bernardes, J. (2014). External uterine contractions signal analysis in relation to labor progression and dystocia. IFMBE Proceedings, 41, 555 - 558.

F

Gonçalves, H., Ayres-de-Campos, D., & Bernardes, J. (2014). Fetal behavioral dynamics in cephalic versus breech presentations. Developmental Psychobiology, 56(7), 1595 - 1600.

Gonçalves, H., Rocha, A. P., Ayres-de-Campos, D., & Bemardes, J. (2008). Frequency domain and entropy analysis of fetal heart rate: Appealing tools for fetal surveillance and pharmacodynamic assessment of drugs. Cardiovascular and Hematological Disorders - Drug TargetsCardiovasc. Hematol. Disord. Drug Targets, 8(2), 91 - 98.

I

Gonçalves, H., Rocha, A. P., Ayres-de-Campos, D., & Bernardes, J. (2006). Internal versus external intrapartum foetal heart rate monitoring: The effect on linear and nonlinear parameters. Physiological MeasurementPhysiol. Meas., 27(3), 307 - 319.

L

Santos, J. M., De Sá, J. M., & Alexandre, L. A. (2008). LEGClust - A clustering algorithm based on layered entropic subgraphs. IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Trans Pattern Anal Mach Intell, 30(1), 62 - 75.

Gonçalves, H., Bernardes, J., Paula Rocha, A., & Ayres-de-Campos, D. (2007). Linear and nonlinear analysis of heart rate patterns associated with fetal behavioral states in the antepartum period. Early Human DevelopmentEarly Hum. Dev., 83(9), 585 - 591.

Gonçalves, H., Rocha, A. P., Ayres-de-Campos, D., & Bernardes, J. (2006). Linear and nonlinear fetal heart rate analysis of normal and acidemic fetuses in the minutes preceding delivery. Medical and Biological Engineering and ComputingMed. Biol. Eng. Comput., 44(10), 847 - 855.

Gonçalves, H., Henriques-Coelho, T., Bernardes, J., Rocha, A. P., Nogueira, A., & Leite-Moreira, A. (2008). Linear and nonlinear heart-rate analysis in a rat model of acute anoxia. Physiological MeasurementPhysiol. Meas., 29(9), 1133 - 1143.

M

Silva, L. M., Marques de Sá, J., & Alexandre, L. A. (2010). The MEE principle in data classification: A perceptron-based analysis. Neural ComputationNeural Comp., 22(10), 2698 - 2728.

N

Santos, J. M., Marques de Sá, J., & Alexandre, L. A. (2005). Neural networks trained with the EEM algorithm: Tuning the smoothing parameter. WSEAS Transactions on SystemsWSEAS Trans. Syst., 4(4), 295 - 299.

De Sá, J. P. M., Sebastião, R., Gama, J., & Fontes, T. (2011). New results on minimum error entropy decision trees. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)Lect. Notes Comput. Sci. (Vol. 7042 LNCS, pp. 355 - 362).

S

Bernardes, J., Gonçalves, H., Ayres-de-Campos, D., & Rocha, A. P. (2009). Sex differences in linear and complex fetal heart rate dynamics of normal and acidemic fetuses in the minutes preceding delivery. Journal of Perinatal MedicineJ. Perinat. Med., 37(2), 168 - 176.

W

Amaral, M., Lopes, M. A., Santos, J. D., & Silva, R. F. (2002). Wettability and surface charge of Si 3N 4-bioglass composites in contact with simulated physiological liquids . BiomaterialsBiomaterials, 23(20), 4123 - 4129.