AI in Mental Health Federated Learning and Privacy
Abstract
This chapter explores the integration of artificial intelligence (AI) in the realm of mental health, focusing on the application of federated learning to ensure privacy and confidentiality. The study delves into the challenges of implementing AI-driven solutions in mental health contexts while prioritizing the protection of sensitive patient information. By leveraging federated learning, a decentralized machine learning approach, the research aims to enhance the accuracy and efficacy of mental health diagnostics without compromising individual privacy. The chapter discusses the potential benefits and ethical considerations associated with the use of AI in mental health, emphasizing the importance of technological advancements.
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