Advancing Pandemic Preparedness in Healthcare 5.0: A Survey of Federated Learning Applications
The intersection of Federated Learning (FL) and Healthcare 5.0 promises a transformative shift towards a more resilient future, particularly concerning pandemic preparedness. Within this context, Healthcare 5.0 signifies a holistic approach to healthcare delivery, where interconnected technologies e...
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| Format: | Article |
| Language: | English |
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Wiley
2023-01-01
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| Series: | Advances in Human-Computer Interaction |
| Online Access: | http://dx.doi.org/10.1155/2023/9992393 |
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| author | Saeed Hamood Alsamhi Ammar Hawbani Alexey V. Shvetsov Santosh Kumar |
| author_facet | Saeed Hamood Alsamhi Ammar Hawbani Alexey V. Shvetsov Santosh Kumar |
| author_sort | Saeed Hamood Alsamhi |
| collection | DOAJ |
| description | The intersection of Federated Learning (FL) and Healthcare 5.0 promises a transformative shift towards a more resilient future, particularly concerning pandemic preparedness. Within this context, Healthcare 5.0 signifies a holistic approach to healthcare delivery, where interconnected technologies enable data-driven decision-making, patient-centric care, and enhanced efficiency. This paper provides an in-depth exploration of FL’s role within the framework of Healthcare 5.0 and its implications for the pandemic response. Specifically, FL offers the potential to revolutionize pandemic preparedness within Healthcare 5.0 in several vital ways: it enables collaborative learning from distributed data sources without compromising individual data privacy, facilitates decentralized decision-making by empowering local healthcare institutions to contribute to a collective knowledge pool, and enhances real-time surveillance, enabling early detection of outbreaks and informed responses. We start by laying out the concepts of FL and Healthcare 5.0, followed by an analysis of current pandemic preparedness and response mechanisms. We delve into FL’s applications and case studies in healthcare, highlighting its potential benefits, including privacy protection, decentralized decision-making, and implementation challenges. By articulating how FL fits into Healthcare 5.0, we envisage future applications in a technologically integrated health system. By examining current applications and case studies of FL in healthcare, we highlight its potential benefits, including enhanced privacy protection and more effective decision support systems. Our findings demonstrate that FL can significantly improve pandemic response times and accuracy. Moreover, we speculate on the potential scenarios where FL could enhance pandemic preparedness and make healthcare more resilient. Finally, we recommend that policymakers, technologists, and educators address potential challenges and maximize the benefits of FL in Healthcare 5.0. This paper aims to contribute to the discourse on next-generation healthcare technologies, emphasizing FL’s potential to shape a more resilient healthcare future. |
| format | Article |
| id | doaj-art-1da54570f165421cbe21725917a7e27f |
| institution | Kabale University |
| issn | 1687-5907 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Human-Computer Interaction |
| spelling | doaj-art-1da54570f165421cbe21725917a7e27f2025-02-03T06:42:54ZengWileyAdvances in Human-Computer Interaction1687-59072023-01-01202310.1155/2023/9992393Advancing Pandemic Preparedness in Healthcare 5.0: A Survey of Federated Learning ApplicationsSaeed Hamood Alsamhi0Ammar Hawbani1Alexey V. Shvetsov2Santosh Kumar3Faculty of EngineeringSchool of Computer and TechnologyDepartment of Smart TechnologiesDepartment of CSEThe intersection of Federated Learning (FL) and Healthcare 5.0 promises a transformative shift towards a more resilient future, particularly concerning pandemic preparedness. Within this context, Healthcare 5.0 signifies a holistic approach to healthcare delivery, where interconnected technologies enable data-driven decision-making, patient-centric care, and enhanced efficiency. This paper provides an in-depth exploration of FL’s role within the framework of Healthcare 5.0 and its implications for the pandemic response. Specifically, FL offers the potential to revolutionize pandemic preparedness within Healthcare 5.0 in several vital ways: it enables collaborative learning from distributed data sources without compromising individual data privacy, facilitates decentralized decision-making by empowering local healthcare institutions to contribute to a collective knowledge pool, and enhances real-time surveillance, enabling early detection of outbreaks and informed responses. We start by laying out the concepts of FL and Healthcare 5.0, followed by an analysis of current pandemic preparedness and response mechanisms. We delve into FL’s applications and case studies in healthcare, highlighting its potential benefits, including privacy protection, decentralized decision-making, and implementation challenges. By articulating how FL fits into Healthcare 5.0, we envisage future applications in a technologically integrated health system. By examining current applications and case studies of FL in healthcare, we highlight its potential benefits, including enhanced privacy protection and more effective decision support systems. Our findings demonstrate that FL can significantly improve pandemic response times and accuracy. Moreover, we speculate on the potential scenarios where FL could enhance pandemic preparedness and make healthcare more resilient. Finally, we recommend that policymakers, technologists, and educators address potential challenges and maximize the benefits of FL in Healthcare 5.0. This paper aims to contribute to the discourse on next-generation healthcare technologies, emphasizing FL’s potential to shape a more resilient healthcare future.http://dx.doi.org/10.1155/2023/9992393 |
| spellingShingle | Saeed Hamood Alsamhi Ammar Hawbani Alexey V. Shvetsov Santosh Kumar Advancing Pandemic Preparedness in Healthcare 5.0: A Survey of Federated Learning Applications Advances in Human-Computer Interaction |
| title | Advancing Pandemic Preparedness in Healthcare 5.0: A Survey of Federated Learning Applications |
| title_full | Advancing Pandemic Preparedness in Healthcare 5.0: A Survey of Federated Learning Applications |
| title_fullStr | Advancing Pandemic Preparedness in Healthcare 5.0: A Survey of Federated Learning Applications |
| title_full_unstemmed | Advancing Pandemic Preparedness in Healthcare 5.0: A Survey of Federated Learning Applications |
| title_short | Advancing Pandemic Preparedness in Healthcare 5.0: A Survey of Federated Learning Applications |
| title_sort | advancing pandemic preparedness in healthcare 5 0 a survey of federated learning applications |
| url | http://dx.doi.org/10.1155/2023/9992393 |
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