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Understanding the prognosis of older adults is a big challenge in healthcare research, especially since very little is known about how different comorbidities interact and influence the prognosis. Recently, a electronic healthcare records dataset of 24 patient attributes from Northwestern Memorial Hospital was used to develop predictive models for five year survival outcome. In this study we analyze...
We present Silverback+, a scalable probabilistic framework for accurate association rule and frequent item-set mining of large-scale social behavioral data. Silverback+ tackles the problem of efficient storage utilization and management via: (1) probabilistic columnar infrastructure and (2) using Bloom filters and sampling techniques. In addition, probabilistic pruning techniques based on Apriori...
We analyze the lung cancer data available from the SEER program with the aim of identifying hotspots using association rule mining techniques. A subset of 13 patient attributes from the SEER data were recently linked with the survival outcome using prediction models, which is used in this study for segmentation. The goal here is to identify characteristics of patient segments where average survival...
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