Cloud-Powered AI Virtual Health Assistants for Effective Patient Query Management and Health Information Access

With the development of fast-growing cloud computing and AI technologies, virtual health assistants' abilities have been greatly improved. To improve access to health information and simplify patient inquiry management, this paper investigates the use of virtual health assistants powered by artificial intelligence (AI) and hosted in the cloud. These virtual assistants can handle patient data, provide real-time personalized health information, and respond to patient requests efficiently and cost-effectively because they operate on primary cloud infrastructure. The proposed approach employs advanced AI technologies such as machine learning and natural language processing (NLP) to understand and resolve various patient inquiries, enhance engagement, and promote improved health outcomes. This technology’s ability to improve patient happiness, decrease response times, and provide accurate information transmission is assessed in the examination. The potential to greatly enhance healthcare service efficiency and efficacy, leading to better patient access and responsiveness.

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Published
2025-06-05
DOI
https://doi.org/10.1109/iccsp64183.2025.11088459
Primary Topic
IoT and Edge/Fog Computing
Type
article
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Cloud-Powered AI Virtual Health Assistants for Effective Patient Query Management and Health Information Access

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Cloud-Powered AI Virtual Health Assistants for Effective Patient Query Management and Health Information Access

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article en

Abstract

With the development of fast-growing cloud computing and AI technologies, virtual health assistants' abilities have been greatly improved. To improve access to health information and simplify patient inquiry management, this paper investigates the use of virtual health assistants powered by artificial intelligence (AI) and hosted in the cloud. These virtual assistants can handle patient data, provide real-time personalized health information, and respond to patient requests efficiently and cost-effectively because they operate on primary cloud infrastructure. The proposed approach employs advanced AI technologies such as machine learning and natural language processing (NLP) to understand and resolve various patient inquiries, enhance engagement, and promote improved health outcomes. This technology’s ability to improve patient happiness, decrease response times, and provide accurate information transmission is assessed in the examination. The potential to greatly enhance healthcare service efficiency and efficacy, leading to better patient access and responsiveness.

Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology (IN), Arunai Engineering College (IN), Ethiopian Public Health Institute (ET), St. Joseph's Institute of Technology (IN), McKinsey & Company (United States) (US)
Openalex Percentile: Top 78%
IoT and Edge/Fog Computing
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