Fossa Skill Optimization Enabled Deep Learning for Medical Big Data Classification in IoT Using Federated Learning

M. Nandini; Deepak N. Biradar

doi:10.1007/s40998-025-00973-5

January 17, 2026Iranian Journal of Science and Technology Transactions of Electrical Engineering

Fossa Skill Optimization Enabled Deep Learning for Medical Big Data Classification in IoT Using Federated Learning

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Key Points

Classification accuracy improves with deep learning models using federated learning techniques in big data.
Key evidence shows a significant increase in performance metrics, illustrating the effectiveness of this approach.
The analysis employs advanced deep learning algorithms to handle large medical datasets in IoT contexts, enhancing data security.
This highlights the need for further exploration into federated learning applications in healthcare, ensuring better patient data management.

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Implication

Observational analysis reveals improved classification accuracy in medical data using federated learning, suggesting a better approach for IoT systems.

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Nandini et al. (2026) studied this question.

synapsesocial.com/papers/69a75a04c6e9836116a1f7c0 https://doi.org/10.1007/s40998-025-00973-5

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Fossa Skill Optimization Enabled Deep Learning for Medical Big Data Classification in IoT Using Federated Learning

Key Points

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Discussion

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Fossa Skill Optimization Enabled Deep Learning for Medical Big Data Classification in IoT Using Federated Learning

Key Points

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Implication

Discussion

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