학술논문

Design of AI in the Health and Elderly Care Service Platform in the Big Data Environment
Document Type
Conference
Source
2023 IEEE International Conference on Paradigm Shift in Information Technologies with Innovative Applications in Global Scenario (ICPSITIAGS) Paradigm Shift in Information Technologies with Innovative Applications in Global Scenario (ICPSITIAGS), 2023 IEEE International Conference on. :111-116 Dec, 2023
Subject
Computing and Processing
Robotics and Control Systems
Machine learning algorithms
Medical services
Big Data
Prediction algorithms
Market research
Real-time systems
Time factors
big data environment
artificial intelligence
healthy elderly care
aging resistant design
Language
Abstract
This electronic document is a “live.” This study aimed to explore the design of AI in the health and elderly care service platform under the big data environment, and analyze its impact on health and elderly care services. By comprehensively utilizing big data and artificial intelligence technology, the intelligent health and elderly care service platform can provide personalized health management, intelligent assisted diagnosis, real-time monitoring and warning, intelligent recommendation and guidance, and data-driven decision support. This study adopted the methods of literature review and experimental analysis to comprehensively analyze and summarize relevant literature and practical cases. The research results indicated that the response time of the platform in this article was between 13-21ms. In the big data environment, AI had significant advantages in the design of health and elderly care service platforms. Through personalized health management, the platform can provide customized health advice and management plans based on users' personal characteristics and health data, improving the accuracy and effectiveness of health management. Intelligent assisted diagnosis utilizes big data analysis and machine learning algorithms to provide doctors with reference for assisted diagnosis and treatment decision-making, improving diagnostic accuracy and efficiency.