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.

Détails bibliographiques
Auteurs principaux: Shafin, Md. Mehtabul Islam, Akhter, Sabrin, Hasan, Mohammad Shafkat, Nasimuzzaman, Md., Prithul, Tamzeedur Rahman
Autres auteurs: Zaman, Shakila
Format: Thèse
Langue:English
Publié: Brac University 2023
Sujets:
Federated learning
Machine learning
e-Health care
CNN
MLP
Random forest
Logistic regression
Medical informatics.
Medical telematics.
Accès en ligne:http://hdl.handle.net/10361/19294

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