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Rare diseases are hard to identify and diagnose. Our goal is to use self-reported behavioural data to distinguish people with rare diseases from people with more common chronic illnesses. To this effect, we adapt a state of the art machine learning algorithm to make this classification. We find that using this method, and an appropriate set of questions, we can accurately identify people with rare...
While many aging in place technologies have been explored in the literature, few have focused on low socioeconomic status (SES) populations. Contextual observations (n=8) were used to gain an in-depth view of the daily needs and challenges of low SES older adults and to provide insights into their experiences of health in and around the home. Our findings have implications not only for the kinds of...
This work-in-progress reports preliminary results of an interview study (n=5) with low SES, rural patients with type 2 diabetes. The paper presents 3 themes and associated design suggestions relating to the high-prevalence of co-morbidities, the importance of external support, and the different stages a patient may be in with respect to making lifestyle changes.
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