The ability to intervene in disease progression given a person’s disease history has the potential to solve one of society’s most pressing issues: advancing health care delivery and reducing its cost. Controlling disease progression is inherently associated with the ability to predict possible future diseases given a patient’s medical history. We invoke an information-theoretic methodology to quantify the level of predictability inherent in disease histories of a large electronic health records dataset with over half a million patients. In our analysis, we progress from zeroth order through temporal informed statistics, both from an individual patient’s standpoint and also considering the collective effects. Our findings confirm our intuition that knowledge of common disease progressions results in higher predictability bounds than treating disease histories independently. We complement this result by showing the point at which the temporal dependence structure vanishes with increasing orders of the time-correlated statistic. Surprisingly, we also show that shuffling individual disease histories only marginally degrades the predictability bounds. This apparent contradiction with respect to the importance of time-ordered information is indicative of the complexities involved in capturing the health-care process and the difficulties associated with utilising this information in universal prediction algorithms.
Abstract-Service-oriented computing is becoming an increasingly popular paradigm for modelling and building distributed systems in heterogeneous, decentralised, and open environments. However, proposed service-oriented architectures are usually based on centralised components, such as service registries or service brokers, that introduce reliability, management, and performance issues. In this paper, we present a fully decentralised service-oriented architecture built on top of a self-organising peer-to-peer infrastructure. This architecture is especially designed to support digital ecosystems due to its low deployment and maintenance cost and inherently decentralised nature.
Abstract-The proliferation of open Internet-scale serviceoriented platforms based on standards, such as WSDL, SOAP and BPEL, enables the composition of independent web services into new value-added services. Such service compositions define the information flows between autonomous and potentially heterogeneous services across the boundaries of independent provider organisations. The availability of individual services in such Digital Ecosystems is likely to be variable due to fluctuating usage load and resource limitations imposed by a service provider's infrastructure. This problem becomes more acute as the number of services in a composition increases. This paper presents a mediation model for improving the availability of composed services. The mediation model masks failures in a service composition by transparently selecting (and executing) an alternative composition at runtime. Service consumers use a common interface to a set of functionally equivalent service compositions while a selection mechanism identifies the most suitable (alternative) service composition. An evaluation of our implementation of the proposed mediation model demonstrates that the consumer perceived availability of value-added services can be improved significantly.
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