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Managing Sensitive Health Data Through Federated Learning and Generative AI Privacy Preserving Techniques: Conversational AI for Patient Engagement Transforming the Future of Healthcare Communication

Managing Sensitive Health Data Through Federated Learning and Generative AI Privacy Preserving Techniques: Conversational AI for Patient Engagement Transforming the Future of Healthcare Communication
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Author(s): Sushmitha Abhishek Rao (School of Business, Indira University, Pune, India), Jaya Saxena (School of Business, Indira University, Pune, India), Sonali Patil (Dr. D.Y. Patil Institute of Management Studies, Akurdi, India)and Komal Singh (National Insurance Academy, Pune, India)
Copyright: 2027
Pages: 22
Source title: Managing Sensitive Health Data Through Federated Learning and Generative AI: Privacy Preserving Techniques
Source Author(s)/Editor(s): Manisha Guduri (Lawrence Technological University, USA), George Pappas (Lawrence Technological University, USA)and Sandeep Thota (Oracle Inc., USA)
DOI: 10.4018/979-8-3373-7426-0.ch013

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Abstract

Conversational Artificial Intelligence (AI), encompassing chatbots, voice assistants, and virtual health companions, is redefining how patients interact with healthcare systems in the digital age. The convergence of AI technologies such as Natural Language Processing (NLP), Machine Learning (ML), and Sentiment Analysis has enabled the creation of intelligent communication interfaces that can understand, interpret, and respond to patient needs in real time. This transformation is not merely technological-it represents a paradigm shift in patient engagement, care continuity, and the overall healthcare experience. In a system traditionally constrained by time, resources, and accessibility, conversational AI provides scalable, personalized, and always-available support, bridging gaps between healthcare providers and patients.

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