Integration of AI and Big Data Analysis with Public Health Systems for Infectious Disease Outbreak Detection
Date
Supervisor
Item type
Conference Contribution
Degree name
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
In an increasingly interconnected world, disease spread has increased, posing devastating consequences for public health. Technologies like wearable devices, social media, Big Data Analysis (BDA), and Artificial Intelligence (AI) offer promising solutions for aiding public health authorities in coping with Infectious Disease Outbreaks (IDOs). The study aims to introduce an integrated framework of AI and BDA with the public health system to detect IDOs and provide valuable insights for prevention, preparation, and response to outbreaks. A systematic review highlighted the improved outbreak control due to AI and BDA but emphasized the need for standardized methods and datasets to enhance AI model accuracy. The proposed framework seeks to overcome these challenges by increasing AI model precision. However, successful integration demands the public health sector to maintain AI development expertise, while healthcare workers must be well-informed about the expanding AI capabilities.Description
Keywords
Source
Rasouli Panah, Hamidreza; Madanian, Samaneh; and Yu, Jian, "Integration of AI and Big Data Analysis with Public Health Systems for Infectious Disease Outbreak Detection" (2023). ACIS 2023 Proceedings. 41. https://aisel.aisnet.org/acis2023/41
DOI
Publisher's version
Rights statement
© 2023 Hamidreza Rasouli Panah, Samaneh Madanian & Jian Yu. This is an open-access article licensed under a Creative Commons Attribution-Non-Commercial 3.0 Australia License, which permits non-commercial use, distribution, and reproduction in any medium, provided the original author and ACIS are credited.