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"Marques, João"

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Faculty of Business and Law

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Brazil

Results 19 resources

Abstracts

Lobo Marques, J. A., & Fong, S. J. (2023). Technology Developments to Face the COVID-19 Pandemic: Advances, Challenges, and Trends. In J. A. Lobo Marques & S. J. Fong (Eds.), Computerized Systems for Diagnosis and Treatment of COVID-19 (pp. 1–13). Springer International Publishing. https://doi.org/10.1007/978-3-031-30788-1_1

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Bernardo Gois, F. N., & Lobo Marques, J. A. (2023). Segmentation of CT-Scan Images Using UNet Network for Patients Diagnosed with COVID-19. In J. A. Lobo Marques & S. J. Fong (Eds.), Computerized Systems for Diagnosis and Treatment of COVID-19 (pp. 29–44). Springer International Publishing. https://doi.org/10.1007/978-3-031-30788-1_3

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Lobo Marques, J. A., & Fong, S. J. (Eds.). (2023). Computerized Systems for Diagnosis and Treatment of COVID-19. Springer International Publishing. https://doi.org/10.1007/978-3-031-30788-1

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Rodrigues, P. M., Madeiro, J. P., & Marques, J. A. L. (2023). Enhancing Health and Public Health through Machine Learning: Decision Support for Smarter Choices. Bioengineering, 10(7), 792. https://doi.org/10.3390/bioengineering10070792

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Bernardo Gois, F. N., Lobo Marques, J. A., & Fong, S. J. (2023). Classification of COVID-19 CT Scans Using Convolutional Neural Networks and Transformers. In J. A. Lobo Marques & S. J. Fong (Eds.), Computerized Systems for Diagnosis and Treatment of COVID-19 (pp. 79–97). Springer International Publishing. https://doi.org/10.1007/978-3-031-30788-1_6

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Bernardo Gois, F. N., Lobo Marques, J. A., & Fong, S. J. (2023). TPOT Automated Machine Learning Approach for Multiple Diagnostic Classification of Lung Radiography and Feature Extraction. In J. A. Lobo Marques & S. J. Fong (Eds.), Computerized Systems for Diagnosis and Treatment of COVID-19 (pp. 117–135). Springer International Publishing. https://doi.org/10.1007/978-3-031-30788-1_8

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Guilherme Cunha Santos, A., Alexandre Lobo Marques, J., Rigo Jr., L., & Paulo Madeiro, J. (2023, November 26). Exploring EEG Signal Features for Predicting Post Cardiac Arrest Prognosis. 2023 Computing in Cardiology Conference. https://doi.org/10.22489/CinC.2023.312

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dos Santos Silva, B. R., Cesar Cortez, P., Crosara Motta, P., & Lobo Marques, J. A. (2023). Covid-19 Detection Based on Chest X-Ray Images Using Multiple Transfer Learning CNN Models. In J. A. Lobo Marques & S. J. Fong (Eds.), Computerized Systems for Diagnosis and Treatment of COVID-19 (pp. 45–63). Springer International Publishing. https://doi.org/10.1007/978-3-031-30788-1_4

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dos Santos Silva, B. R., Cortez, P. C., da Silva Neto, M. G., & Lobo Marques, J. A. (2023). X-Ray Machine Learning Classification with VGG-16 for Feature Extraction. In J. A. Lobo Marques & S. J. Fong (Eds.), Computerized Systems for Diagnosis and Treatment of COVID-19 (pp. 65–78). Springer International Publishing. https://doi.org/10.1007/978-3-031-30788-1_5

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Motta, P. C., Cesar Cortez, P., & Lobo Marques, J. A. (2023). COVID-19 Classification Using CT Scans with Convolutional Neural Networks. In J. A. Lobo Marques & S. J. Fong (Eds.), Computerized Systems for Diagnosis and Treatment of COVID-19 (pp. 99–116). Springer International Publishing. https://doi.org/10.1007/978-3-031-30788-1_7

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Pordeus, D., Ribeiro, P., Zacarias, L., Paulo Madeiro, J., Lobo Marques, J. A., Miguel Rodrigues, P., Leite, C., Alves Neto, M., Aires Peixoto Jr, A., & de Oliveira, A. (2023). Classification of Severity of COVID-19 Patients Based on the Heart Rate Variability. In J. A. Lobo Marques & S. J. Fong (Eds.), Computerized Systems for Diagnosis and Treatment of COVID-19 (pp. 155–177). Springer International Publishing. https://doi.org/10.1007/978-3-031-30788-1_10

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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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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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Goncalves, M., Lobo Marques, J. A., Silva, B. R. S., Luther, V., & Hayes, S. (2023). Neuromarketing and Global Branding Reaction Analysis Based on Real-Time Monitoring of Multiple Consumer’s Biosignals and Emotions. Journal of International Business and Management, 6(5), 01–32. https://doi.org/10.37227/JIBM-2023-04-5912

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dos Santos Silva, B. R., Cesar Cortez, P., Gomes Aguiar, R., Rodrigues Ribeiro, T., Pereira Teixeira, A., Bernardo Gois, F. N., & Lobo Marques, J. A. (2023). Lung Segmentation of Chest X-Rays Using Unet Convolutional Networks. In J. A. Lobo Marques & S. J. Fong (Eds.), Computerized Systems for Diagnosis and Treatment of COVID-19 (pp. 15–28). Springer International Publishing. https://doi.org/10.1007/978-3-031-30788-1_2

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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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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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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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Pordeus, D., Ribeiro, P., Zacarias, L., de Oliveira, A., Marques, J. A. L., Rodrigues, P. M., Leite, C., Neto, M. A., Peixoto, A. A., & do Vale Madeiro, J. P. (2023). Training Strategies for Covid-19 Severity Classification. In I. Rojas, O. Valenzuela, F. Rojas Ruiz, L. J. Herrera, & F. Ortuño (Eds.), Bioinformatics and Biomedical Engineering (pp. 514–527). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-34953-9_40

Last update from database: 10/30/25, 7:01 PM (UTC)