The lives of many thousands of children born premature or ill at term around the world have been saved by those who work within neonatal intensive care units (NICUs). Modern-day neonatologists, together with nursing staff and other specialists within this domain, enjoy modern technologies for activities such as financial transactions, online purchasing, music, and video on demand. Yet, when they move into their workspace, in many cases, they are supported by nearly the same technology they used 20 years ago. Medical devices provide visual displays of vital signs through physiological streams such as electrocardiogram (ECG), heart rate, blood oxygen saturation (SpO(2)), and respiratory rate. Electronic health record initiatives around the world provide an environment for the electronic management of medical records, but they fail to support the high-frequency interpretation of streaming physiological data. We have taken a collaborative research approach to address this need to provide a flexible platform for the real-time online analysis of patients' data streams to detect medically significant conditions that precede the onset of medical complications. The platform supports automated or clinician-driven knowledge discovery to discover new relationships between physiological data stream events and latent medical conditions as well as to refine existing analytics. Patients benefit from the system because earlier detection of signs of the medical conditions may lead to earlier intervention that may potentially lead to improved patient outcomes and reduced length of stays. The clinician benefits from a decision support tool that provides insight into multiple streams of data that are too voluminous to assess with traditional methods. The remainder of this article summarizes the strengths of our research collaboration and the resulting environment known as Artemis, which is currently being piloted within the NICU of The Hospital for Sick Children (SickKids) in Toronto, Ontario, Canada. Although the discussion in this article focuses on a NICU, the technologies can be applied to any intensive care environment.

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Laptop learning programs have been developed to create ubiquitous online learning environments. Given the infancy of many programs, there is little understanding of aspects of the program are perceived to provide value to faculty and students. This paper focuses on the value proposition (with respect to perceived benefits versus capital investment) for undergraduate students in a mandatory, campus-wide, comprehensive laptop learning program. Results indicate that the perceived value of the laptop for technical programs such as science, engineering, and information technology, and liberal arts programs such as business and criminology, justice, and policy studies are significantly different. This difference results in a clear need to use different laptop learning models for each type of program and that a single campus-wide model will likely prove unsatisfactory for most students. A need to better communicate the true value of industry-specific software and skills acquisition is also highlighted.

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