Application of Federated Learning and Gestural Technology in Healthcare

Abstract

This chapter explores the integration of federated learning and gestural technology in the healthcare sector, aiming to enhance patient care, diagnostics, and treatment. Federated learning allows decentralized machine learning models to train on patient data from multiple healthcare institutions while maintaining privacy, making it ideal for protecting sensitive medical data. Gestural technology is mainly utilized in human-computer interaction to assist healthcare professionals in the management of accessibility and usability of healthcare systems, especially during remote diagnostics and rehabilitation. The integration of these two technologies ensures that individualized care can be achieved, workflow operations streamlined, and outcomes improved without compromising data security. It also explores use cases of telemedicine, rehabilitation, and clinical decision support, addressing challenges like data privacy, model accuracy, and technical integration.

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