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- W4286307995 abstract "Social isolation is a serious public health issue that can lead to various mental and physical health problems for individuals and jeopardizes their life's quality. The issue is more critical for older adults and palliative patients who are already suffering from different diseases and lack some abilities for performing their daily tasks. Additionally, this situation worsens when the COVID-19 pandemic adds forced social isolation to people's lives worldwide. In this paper, we propose a framework for detecting social isolation in community-based palliative care networks. We look at the problem as an outlier detection in community-based social graphs. Hence, we map the network to an attributed weighted social graph. Consequently, each patient is linked to a set of informal and formal care providers. We define formulae and indices to extract the norm of the society in terms of structural connections and assign a value to each individual based on the quality and quantity of its connections. The structural indices and a set of quality of life features such as age, marital status, life satisfaction, and capabilities are then used to identify the isolated individuals. We analyze and evaluate the performance of our algorithm on real-life data obtained by the Windsor Essex Compassion Care Community (WECCC), as well as various synthetic social graphs." @default.
- W4286307995 created "2022-07-21" @default.
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- W4286307995 date "2022-05-01" @default.
- W4286307995 modified "2023-09-29" @default.
- W4286307995 title "Social Isolation Detection in Palliative Care using Social Network Analysis" @default.
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- W4286307995 doi "https://doi.org/10.1109/ccgrid54584.2022.00109" @default.
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