Automatic generation of textual summaries from neonatal intensive care data
Artificial Intelligence
Facilitating benign deceit in mediated communication
CHI '09 Extended Abstracts on Human Factors in Computing Systems
IEEE Transactions on Information Technology in Biomedicine - Special section on affective and pervasive computing for healthcare
Layered evaluation of interactive adaptive systems: framework and formative methods
User Modeling and User-Adapted Interaction
Using mobile phones to present medical information to hospital patients
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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There is a vast amount of data associated with any one patient. It is challenging for medical staff to understand all this data. It is even harder for a lay person, who may not even know what medical terms mean. The research project BabyTalk-Clan aims to create personalized summaries of data for a lay audience. It uses sensitive, highly-detailed clinical data relating to a patient. This includes medication given, test results, notes made by medical staff, and continuous physiological signals such as heart rate. We took a qualitative approach to knowledge acquisition for user requirements. Using interviews and a focus group within a Grounded Theory methodology, we discovered that most lay users want only a very high-level summary of the baby's state. What lay users do want is information about how the parents are coping, and what support they need. Findings were cross-validated through a questionnaire.