Kioskli, Kitty and Papastergiou, Spyridon (2023) A Swarm Artificial Intelligence Approach for Effective Treatment of Chronic Conditions. In: 2023 19th International Conference on the Design of Reliable Communication Networks (DRCN), 2023-04-17 - 2023-04-20, Vilanova i la Geltru, Spain.
Kioskli, Kitty and Papastergiou, Spyridon (2023) A Swarm Artificial Intelligence Approach for Effective Treatment of Chronic Conditions. In: 2023 19th International Conference on the Design of Reliable Communication Networks (DRCN), 2023-04-17 - 2023-04-20, Vilanova i la Geltru, Spain.
Kioskli, Kitty and Papastergiou, Spyridon (2023) A Swarm Artificial Intelligence Approach for Effective Treatment of Chronic Conditions. In: 2023 19th International Conference on the Design of Reliable Communication Networks (DRCN), 2023-04-17 - 2023-04-20, Vilanova i la Geltru, Spain.
Abstract
Long-term conditions or chronic diseases are multifaceted and challenging. Current treatment options, for patients with long-term conditions, are mainly pharmacological, causing numerous adverse drug events and pressing for alternative management strategies such as personalized interventions. Areas of machine learning, such as deep learning, would enable researchers to develop predictive modelling algorithms, using continuous monitoring and allowing assessing the medical risk for long-term conditions and their related complications. In this paper, we claim that harmonization of data, novel machine learning algorithms, swarm-based technologies, and the involvement of the entire healthcare community will lead to acceptable and effective personalized healthcare. Our proposed approach aims to amplify the intelligence of the healthcare community. Based upon the patients’ characteristics empowers better decisions, personalised medical risk prediction and recommendations of acceptable and effective interventions. Our future work includes the validation of the SwarmAI framework by actively engaging relevant stakeholders.
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Uncontrolled Keywords: | swarm intelligence; artificial intelligence; cybersecurity; personalized healthcare; long-term conditions |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 17 Oct 2024 19:17 |
Last Modified: | 11 Nov 2024 17:58 |
URI: | http://repository.essex.ac.uk/id/eprint/35482 |
Available files
Filename: Kioskli&Papastergiou, 2023.pdf