| Autor: |
Hsien-Ming Chou |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
|
| Zdroj: |
IEEE Access, Vol 8, Pp 43657-43664 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2020.2977043 |
| Popis: |
The trend of aging population among working families has made health care services for sub-healthy people more important. In Taiwan, caregivers are often hired by human resource agencies to provide long-term care, and they are the main supervisors responsible for the care of the sub-healthy people. However, most agencies only consider the cost of their caregivers and have insufficient staff to take care of the sub-healthy people, leading to the failure of the long-term care system. The lack of an effective collaborative framework for long-term care leads to sub-healthy people being at high risks. Existing frameworks for long-term care are still in the early stages of capturing suitability information dynamically. This paper proposes a new framework that includes all possible features suitable to support the needs of all sub-healthy people and provides a solution for the issue of determining suitable features for collaboration. This study applies association rules to long-term care to handle the mapping process and uses artificial intelligence technology to solve the issues of adjusting human variability dynamically based on the mapping result of sub-healthy people. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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