Privacy preserving epileptic seizure recognition using federated and explainable machine learning

Key Points

• Seizure recognition accuracy improved significantly with the use of federated learning and explainable AI techniques.
• Key evidence shows a marked increase in accuracy rates by 25% compared to traditional methods.
• Assessment using advanced machine learning models facilitated the analysis of diverse patient data without compromising privacy.
• Highlights the importance of privacy-preserving techniques in sensitive health data management, calling for more studies in this area.