Analyzing the security of e-Health data based on a hybrid federated learning model

Analyzing the security of e-Health data based on a hybrid federated learning model

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023.

Dettagli Bibliografici
Autori principali:	Shafin, Md. Mehtabul Islam, Akhter, Sabrin, Hasan, Mohammad Shafkat, Nasimuzzaman, Md., Prithul, Tamzeedur Rahman
Altri autori:	Zaman, Shakila
Natura:	Tesi
Lingua:	English
Pubblicazione:	Brac University 2023
Soggetti:	Federated learning Machine learning e-Health care CNN MLP Random forest Logistic regression Medical informatics. Medical telematics.
Accesso online:	http://hdl.handle.net/10361/19294

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