Julie S. Weber

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We present a new algorithm for active learning embedded within an interactive calendar management system that learns its users' scheduling preferences. When the system receives a meeting request, the active learner selects a set of alternative solutions to present to the user; learning is then achieved by noting the user's preferences for the selected(More)
OBJECTIVE To describe the underlying clinical decision-making rationale among general pediatricians, family physicians, pediatric cardiologists and pediatric nephrologists in their approach to an adolescent with hypertension. METHODS We conducted semi-structured phone interviews with a convenience sample of physicians from the above-mentioned 4(More)
We are developing an adaptive reminding system that tailors its reminders to its users' reminding preferences through real-time interaction and feedback. To determine the potential utility of such a system, we conducted a multi-phase user study, presented in this paper, in which we evaluate people's preferences for the visual presentation of reminders.(More)
Introduction We discuss the problem of creating a reminder generation system that successfully alerts a user to daily tasks while adapting the features of its reminders to the user’s reminding preferences. There are many example applications in which reminding is useful; we motivate the discussion by focusing on two such applications. The first is an office(More)
We describe a simulation system that models the user of a calendar-management tool. The tool is intended to learn the user's scheduling preferences, and we employ the simulator to evaluate learning strategies. The simulated user is instantiated with a set of preferences over local and global features of a schedule such as the level of importance of a(More)
OBJECTIVE To determine whether using emergency department (ED) virtual observation for select pediatric conditions decreases admission rates for these conditions, and to examine effects on length of stay. METHODS The option of ED virtual observation care for 9 common pediatric conditions was introduced in 2009; associated order sets were developed.(More)
We present a new algorithm for active learning within an interactive calendar management system that learns its users’ scheduling preferences. This application imposes certain constraints on the active learning process. Most notably, arbitrary examples cannot be presented for labeling by the user; instead, labeling opportunities arise only when the system(More)
This extended abstract describes ongoing work in the development of an intelligent assistant that interacts with its user in a personalized fashion, deciding whether, when and how to interact based on a user’s needs and preferences. I consider two types of users: people who work in an office environment and require assistance with managing their daily(More)
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