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Different software reliability models can produce very different answers when called on to predict future reliability in a reliability growth context. Users need to know which, if any, of the competing predictions are trustworthy. Some techniques are presented which form the basis of a partial solution to this problem. Rather than attempting to decide which(More)
In spite of much research effort, there is no universally applicable software reliability growth model which can be trusted to give accurate predictions of reliability in all circumstances. Worse, we are not even in a position to be able to decide a priori which of the many models is most suitable in a particular context. Our own recent work has tried to(More)
BACKGROUND Untreated metastatic uveal melanoma (UM) carries a grave prognosis. Unlike cutaneous melanoma (CM), there are no established treatments known to significantly improve outcomes for a meaningful proportion of patients. Inhibition of the PD1-PDL1 axis has shown promise in the management of CM and we here report a two center experience of UM patients(More)
INTRODUCTION Electronic health records (EHRs) can potentially extend chronic disease surveillance, but few EHR-based initiatives tracking population-based metrics have been validated for accuracy. We designed a new EHR-based population health surveillance system for New York City (NYC) known as NYC Macroscope. This report is the third in a 3-part series(More)
INTRODUCTION Electronic health records (EHRs) offer potential for population health surveillance but EHR-based surveillance measures require validation prior to use. We assessed the validity of obesity, smoking, depression, and influenza vaccination indicators from a new EHR surveillance system, the New York City (NYC) Macroscope. This report is the second(More)
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