38 research outputs found

    Interrogating Biosensing in Everyday Life

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    The Empirical Foundations of Telemedicine Interventions in Primary Care

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    Introduction: This article presents the scientific evidence for the merits of telemedicine interventions in primary care. Although there is no uniform and consistent definition of primary care, most agree that it occupies a central role in the healthcare system as first contact for patients seeking care, as well as gatekeeper and coordinator of care. It enables and supports patient-centered care, the medical home, managed care, accountable care, and population health. Increasing concerns about sustainability and the anticipated shortages of primary care physicians have sparked interest in exploring the potential of telemedicine in addressing many of the challenges facing primary care in the United States and the world. Materials and Methods: The findings are based on a systematic review of scientific studies published from 2005 through 2015. The initial search yielded 2,308 articles, with 86 meeting the inclusion criteria. Evidence is organized and evaluated according to feasibility/acceptance, intermediate outcomes, health outcomes, and cost. Results: The majority of studies support the feasibility/acceptance of telemedicine for use in primary care, although it varies significantly by demographic variables, such as gender, age, and socioeconomic status, and telemedicine has often been found more acceptable by patients than healthcare providers. Outcomes data are limited but overall suggest that telemedicine interventions are generally at least as effective as traditional care. Cost analyses vary, but telemedicine in primary care is increasingly demonstrated to be cost-effective. Conclusions: Telemedicine has significant potential to address many of the challenges facing primary care in today's healthcare environment. Challenges still remain in validating its impact on clinical outcomes with scientific rigor, as well as in standardizing methods to assess cost, but patient and provider acceptance is increasingly making telemedicine a viable and integral component of primary care around the world.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140293/1/tmj.2016.0045.pd

    Designing with biosignals: Challenges, opportunities, and future directions for integrating physiological signals in human-computer interaction

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    Biosensing technologies are a rapidly increasing presence in our daily lives. These sensor-based technologies measure physiological processes including heart rate, breathing, skin conductance, brain activity and more. Researchers are exploring biosensing from perspectives including: engineering, human-computer interaction, medicine, mental health, consumer products, and interactive art. These technologies can enhance our interactions allowing connection to our bodies and others around us across diverse application areas. However, designing with biosignals in Human-Computer Interaction presents new challenges pertaining to User Experience, Input/Output, interpretation of signals, representation, and ethics. There is an urgent need to build a scholarly community that includes the diverse perspectives of researchers, designers, industry practitioners and policymakers. The goal of this workshop is to leverage the knowledge of this community aiming to map out the research landscape of emerging challenges and opportunities, and to build a research agenda for future directions

    Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses.

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    Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype1-3. To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. We identified 32 novel susceptibility loci (P < 5.0 × 10-8), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate < 0.05). Five loci showed associations (P < 0.05) in opposite directions between luminal and non-luminal subtypes. In silico analyses showed that these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 54.2% for luminal A-like disease and 37.6% for triple-negative disease. The odds ratios of polygenic risk scores, which included 330 variants, for the highest 1% of quantiles compared with middle quantiles were 5.63 and 3.02 for luminal A-like and triple-negative disease, respectively. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores
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