@inproceedings{bfb128611b6443619644a57002fde893,
title = "A statistical reasoning system for medication prompting",
abstract = "We describe our experience building and using a reasoning system for providing context-based prompts to elders to take their medication. We describe the process of specification, design, implementation and use of our system. We chose a simple Dynamic Bayesian Network as our representation. We analyze the design space for the model in some detail. A key challenge in using the model was the overhead of labeling the data. We analyze the impact of a variety of options to ease labeling, and highlight in particular the utility of simple clustering before labeling. A key choice in the design of such reasoning systems is that between statistical and deterministic rule-based approaches. We evaluate a simple rule-based system on our data and discuss some of its pros and cons when compared to the statistical (Bayesian) approach in a practical setting. We discuss challenges to reasoning arising from failures of data collection procedures and calibration drift. The system was deployed among 6 subjects over a period of 12 weeks, and resulted in adherence improving from 56% on average with no prompting to 63% with state of the art context-unaware prompts to 74% with our context-aware prompts.",
author = "Sengul Vurgun and Matthai Philipose and Misha Pavel",
year = "2007",
doi = "10.1007/978-3-540-74853-3_1",
language = "English (US)",
isbn = "3540748520",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer-Verlag",
pages = "1--18",
booktitle = "UbiComp 2007",
note = "9th International Conference on Ubiquitous Computing, UbiComp 2007 ; Conference date: 16-09-2007 Through 19-09-2007",
}