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In authors or contributors

"Joao, Alexandre Lobo Marques"

Publication year

Between 2000 and 2025
- Between 2020 and 2025

Results 102 resources

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Abstracts

Ribeiro, P., Pordeus, D., Zacarias, L., Leite, C., Alves Neto, M., Aires Peixoto Jr, A., de Oliveira, A., Paulo Madeiro, J., Lobo Marques, J. A., & Miguel Rodrigues, P. (2023). Evaluation of ECG Non-linear Features in Time-Frequency Domain for the Discrimination of COVID-19 Severity Stages. In J. A. Lobo Marques & S. J. Fong (Eds.), Computerized Systems for Diagnosis and Treatment of COVID-19 (pp. 137–154). Springer International Publishing. https://doi.org/10.1007/978-3-031-30788-1_9

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Goncalves, M. V., Marques, J. A. L., Silva, B. R. S., Luther, V., & Hayes, S. (2022). Neuromarketing and Global Branding Reaction Analysis Based on Real-Time Monitoring of Multiple Consumer’s Biosignals and Emotions (SSRN Scholarly Paper No. 4071297). https://doi.org/10.2139/ssrn.4071297

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Silva, S. C. e, Machado, J. C., Martins, C., Duarte, P., & Marques, J. A. L. (2021). Modelling the barriers that are preventing e-commerce to thrive – a case study from Portugal, international journal of business excellence. International Journal of Business Excellence.
Yan, K., Lam, C. F., Fong, S., Lobo Marques, J. A., Song, Q., & Qin, H. (2024). Enhancing Dynamic Hand Gesture Recognition through Optimized Feature Selection using Double Machine Learning. Proceedings of the 2024 8th International Conference on Big Data and Internet of Things, 19–25. https://doi.org/10.1145/3697355.3697359

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Ip, C. H., Lobo Marques, J. A., Dos Santos Silva, B. R., Cortez, P. C., & Barbosa, A. (2023). A Review on Open Innovation and Absorptive Capacity in Small and Medium Enterprises during the last decade - Analyzing Bibliometrics to Understand the Development of the Field. Proceedings of the 2023 14th International Conference on E-Business, Management and Economics, 417–422. https://doi.org/10.1145/3616712.3616786

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Yan, K., Lam, C.-F., Fong, S., Lobo Marques, J. A., Millham, R. C., & Mohammed, S. (2025). A Novel Improvement of Feature Selection for Dynamic Hand Gesture Identification Based on Double Machine Learning. Sensors, 25(4), 1–21. https://doi.org/10.3390/s25041126

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Albuquerque, V., Gois, F. B., Lobo Marques, J. A., Silva, B. R. dos S., & Cortez, P. C. (2024). Automl-Based Eeg Signal Analysis in Neuro-Marketing Classification Using Biclustering Method. 1–29. https://doi.org/10.2139/ssrn.4871053

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Fernandes, J. V. M. R., Alexandria, A. R. de, Lobo Marques, J. A., Assis, D. F. de, Motta, P. C., & Silva, B. R. dos S. (2024). Emotion Detection from EEG Signals Using Machine Deep Learning Models. Bioengineering, 11(8), 782. https://doi.org/10.3390/bioengineering11080782

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Caldas, W. L., Do Vale Madeiro, J. P., Pedrosa, R. C., Gomes, J. P. P., Du, W., & Marques, J. A. L. (2023). Noise Detection and Classification in Chagasic ECG Signals Based on One-Dimensional Convolutional Neural Networks. In R. Lee (Ed.), Computer and Information Science (Vol. 1055, pp. 117–129). Springer International Publishing. https://doi.org/10.1007/978-3-031-12127-2_8

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Caldas, W. L., do Vale Madeiro, J. P., Pedrosa, R. C., Gomes, J. P. P., Du, W., & Marques, J. A. L. (2023). Noise Detection and Classification in Chagasic ECG Signals Based on One-Dimensional Convolutional Neural Networks. In R. Lee (Ed.), Computer and Information Science (pp. 117–129). Springer International Publishing. https://doi.org/10.1007/978-3-031-12127-2_8

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Lobo Marques, J. A., Macedo, D. S., Motta, P., dos Santos Silva, B. R., Carvalho, F. H. C., Kehdi, R. C., Cavalcante, L. R. L., da Silva Viana, M., Lós, D., & Fiorenza, N. G. (2023). Exploratory Data Analysis on Clinical and Emotional Parameters of Pregnant Women with COVID-19 Symptoms. In J. A. Lobo Marques & S. J. Fong (Eds.), Computerized Systems for Diagnosis and Treatment of COVID-19 (pp. 179–209). Springer International Publishing. https://doi.org/10.1007/978-3-031-30788-1_11

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Filho, E. M. L., Silveira, A. B., Ferreira, A. M., Lobo Marques, J. A., Batista, J. G., Guimarães, G. D. F., Alexandria, A. R. D., & Rodrigues, J. J. P. C. (2024, November 6). Optimization of Energy Storage Systems with Renewable Energy Generation and Consumption Data. 2024 IEEE 7th Student Conference on Electric Machines and Systems (SCEMS). 2024 IEEE 7th Student Conference on Electric Machines and Systems (SCEMS). https://doi.org/10.1109/SCEMS63294.2024.10756498

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Marques, J. A. L., Gois, F. N. B., Madeiro, J. P. do V., Li, T., & Fong, S. J. (2022). Artificial neural network-based approaches for computer-aided disease diagnosis and treatment. In A. K. Bhoi, V. H. C. de Albuquerque, P. N. Srinivasu, & G. Marques (Eds.), Cognitive and Soft Computing Techniques for the Analysis of Healthcare Data (pp. 79–99). Academic Press. https://doi.org/10.1016/B978-0-323-85751-2.00008-6

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Marques, J. A. L., Han, T., Wu, W., Madeiro, J. P. do V., Neto, A. V. L., Gravina, R., Fortino, G., & de Albuquerque, V. H. C. (2021). IoT-Based Smart Health System for Ambulatory Maternal and Fetal Monitoring. IEEE Internet of Things Journal, 8(23), 16814–16824. https://doi.org/10.1109/JIOT.2020.3037759
Ribeiro, P., de Souza, C. C. C., Camerino, C. M. C., Pordeus, D., Leite, C. F., Lobo Marques, J. A., Madeiro, J. P., & Rodrigues, P. M. (2024). Assessment of the post-acute COVID-19 syndrome cardiovascular effect through ECG analysis. https://dspace.usj.edu.mo/handle/123456789/6383

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Lôbo Marques, J. A., Bernardo Gois, F. N., Nunes da Silveira, J. A., Li, T., & Fong, S. J. (2022). AI and deep learning for processing the huge amount of patient-centric data that assist in clinical decisions. In A. K. Bhoi, V. H. C. de Albuquerque, P. N. Srinivasu, & G. Marques (Eds.), Cognitive and Soft Computing Techniques for the Analysis of Healthcare Data (pp. 101–121). Academic Press. https://doi.org/10.1016/B978-0-323-85751-2.00001-3

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Ribeiro, P., Marques, J. A. L., Pordeus, D., Zacarias, L., Leite, C. F., Sobreira-Neto, M. A., Peixoto, A. A., de Oliveira, A., Madeiro, J. P. do V., & Rodrigues, P. M. (2024). Machine learning-based cardiac activity non-linear analysis for discriminating COVID-19 patients with different degrees of severity. Biomedical Signal Processing and Control, 87, 105558. https://doi.org/10.1016/j.bspc.2023.105558

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Gois, F. N. B., Marques, J. A. L., de Oliveira Dantas, A. B., Santos, M. C., Neto, J. V. S., de Macêdo, J. A. F., Du, W., & Li, Y. (2023). Malaria Blood Smears Object Detection Based on Convolutional DCGAN and CNN Deep Learning Architectures. In R. Lee (Ed.), Computer and Information Science (pp. 197–212). Springer International Publishing. https://doi.org/10.1007/978-3-031-12127-2_14

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Gois, F. N. B., Marques, J. A. L., De Oliveira Dantas, A. B., Santos, M. C., Neto, J. V. S., De Macêdo, J. A. F., Du, W., & Li, Y. (2023). Malaria Blood Smears Object Detection Based on Convolutional DCGAN and CNN Deep Learning Architectures. In R. Lee (Ed.), Computer and Information Science (Vol. 1055, pp. 197–212). Springer International Publishing. https://doi.org/10.1007/978-3-031-12127-2_14

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Barbosa, R. L., Martins, H. de C. T. e, Barbosa, F. C., da Costa, B. T., Matela, R. F., Neto, J. F. R. F., Fontes, Y. N. S., Lobo Marques, J. A., Duarte, J. B. F., & Neto, J. S. da C. (2024). Doctor Bone: treinamento de redes neurais para auxílio na identificação da idade óssea. 16 (Especial), 1–16. https://doi.org/10.59681/2175-4411.v16.iEspecial.2024.13821

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Last update from database: 6/5/25, 12:01 PM (UTC)