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Artigo de periodico
Advances in application of federated machine learning for oncology and cancer diagnosis (2025)
Nasajpour, Mohammad ; Pouriyeh, Seyedamin ; Parizi, Reza M ; Han, Meng ; Mosaiyebzadeh, Fatemeh ; Xie, Yixin ; Liu, Liyuan ; Batista, Daniel Macêdo
Source: Information. Unidade: IME
Subjects: APRENDIZADO COMPUTACIONAL, DIAGNÓSTICO, ONCOLOGIA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
NASAJPOUR, Mohammad et al. Advances in application of federated machine learning for oncology and cancer diagnosis. Information, v. 16, n. artigo 487, p. 1-31, 2025Tradução . . Disponível em: https://doi.org/10.3390/info16060487. Acesso em: 27 nov. 2025.
APA
Nasajpour, M., Pouriyeh, S., Parizi, R. M., Han, M., Mosaiyebzadeh, F., Xie, Y., et al. (2025). Advances in application of federated machine learning for oncology and cancer diagnosis. Information, 16( artigo 487), 1-31. doi:10.3390/info16060487
NLM
Nasajpour M, Pouriyeh S, Parizi RM, Han M, Mosaiyebzadeh F, Xie Y, Liu L, Batista DM. Advances in application of federated machine learning for oncology and cancer diagnosis [Internet]. Information. 2025 ; 16( artigo 487): 1-31.[citado 2025 nov. 27 ] Available from: https://doi.org/10.3390/info16060487
Vancouver
Nasajpour M, Pouriyeh S, Parizi RM, Han M, Mosaiyebzadeh F, Xie Y, Liu L, Batista DM. Advances in application of federated machine learning for oncology and cancer diagnosis [Internet]. Information. 2025 ; 16( artigo 487): 1-31.[citado 2025 nov. 27 ] Available from: https://doi.org/10.3390/info16060487
Artigo de periodico
Federated learning in smart healthcare: a survey of applications, challenges, and future directions (2025)
Nasajpour, Mohammad ; Pouriyeh, Seyedamin ; Parizi, Reza M. ; Han, Meng ; Mosaiyebzadeh, Fatemeh ; Liu, Liyuan ; Xie, Yixin ; Batista, Daniel Macêdo
Source: Electronics. Unidade: IME
Subjects: INTERNET DAS COISAS, APRENDIZAGEM PROFUNDA, INTELIGÊNCIA ARTIFICIAL, ASSISTÊNCIA À SAÚDE
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
NASAJPOUR, Mohammad et al. Federated learning in smart healthcare: a survey of applications, challenges, and future directions. Electronics, v. 14, n. artigo 1750, p. 1-40, 2025Tradução . . Disponível em: https://doi.org/10.3390/electronics14091750. Acesso em: 27 nov. 2025.
APA
Nasajpour, M., Pouriyeh, S., Parizi, R. M., Han, M., Mosaiyebzadeh, F., Liu, L., et al. (2025). Federated learning in smart healthcare: a survey of applications, challenges, and future directions. Electronics, 14( artigo 1750), 1-40. doi:10.3390/electronics14091750
NLM
Nasajpour M, Pouriyeh S, Parizi RM, Han M, Mosaiyebzadeh F, Liu L, Xie Y, Batista DM. Federated learning in smart healthcare: a survey of applications, challenges, and future directions [Internet]. Electronics. 2025 ; 14( artigo 1750): 1-40.[citado 2025 nov. 27 ] Available from: https://doi.org/10.3390/electronics14091750
Vancouver
Nasajpour M, Pouriyeh S, Parizi RM, Han M, Mosaiyebzadeh F, Liu L, Xie Y, Batista DM. Federated learning in smart healthcare: a survey of applications, challenges, and future directions [Internet]. Electronics. 2025 ; 14( artigo 1750): 1-40.[citado 2025 nov. 27 ] Available from: https://doi.org/10.3390/electronics14091750
Artigo de periodico
Privacy-preserving federated learning-based intrusion detection system for IoHT devices (2025)
Mosaiyebzadeh, Fatemeh ; Pouriyeh, Seyedamin ; Han, Meng ; Liu, Liyuan ; Xie, Yixin ; Zhao, Liang ; Batista, Daniel Macêdo
Source: Electronics. Unidade: IME
Subjects: INTERNET DAS COISAS, APRENDIZAGEM PROFUNDA, AVALIAÇÃO DE DESEMPENHO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MOSAIYEBZADEH, Fatemeh et al. Privacy-preserving federated learning-based intrusion detection system for IoHT devices. Electronics, v. 14, n. artigo 67, p. 1-18, 2025Tradução . . Disponível em: https://doi.org/10.3390/electronics14010067. Acesso em: 27 nov. 2025.
APA
Mosaiyebzadeh, F., Pouriyeh, S., Han, M., Liu, L., Xie, Y., Zhao, L., & Batista, D. M. (2025). Privacy-preserving federated learning-based intrusion detection system for IoHT devices. Electronics, 14( artigo 67), 1-18. doi:10.3390/electronics14010067
NLM
Mosaiyebzadeh F, Pouriyeh S, Han M, Liu L, Xie Y, Zhao L, Batista DM. Privacy-preserving federated learning-based intrusion detection system for IoHT devices [Internet]. Electronics. 2025 ; 14( artigo 67): 1-18.[citado 2025 nov. 27 ] Available from: https://doi.org/10.3390/electronics14010067
Vancouver
Mosaiyebzadeh F, Pouriyeh S, Han M, Liu L, Xie Y, Zhao L, Batista DM. Privacy-preserving federated learning-based intrusion detection system for IoHT devices [Internet]. Electronics. 2025 ; 14( artigo 67): 1-18.[citado 2025 nov. 27 ] Available from: https://doi.org/10.3390/electronics14010067

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