Feature Based Rule Learner in Noisy Environment Using Neighbourhood Rough Set Model
International Journal of Software Science and Computational Intelligence
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The purpose of this paper is to describe a recent project in which Internet-ready handheld computers (Personal Digital Assistants, PDAs) and custom software applications were used to help diabetes patients self manage their condition. The project research team is made up of professors and graduate students with backgrounds in information technology, nursing, and sociology who have an interest in using emerging technologies in healthcare applications. The researchers theorized that allowing diabetes patients to easily enter information about their daily activities (e.g. diet, exercise, blood sugar levels, and medications) into a handheld computer, and then immediately use a wireless network connection to upload that information to a central server for review by a medical professional would prove more useful than simply logging this information for the patient's own use. A seed grant was acquired, computer hardware was purchased, and a prototype system was developed. Thirteen individuals tested the prototype system and the users were qualitatively interviewed. The users were also presented with a 10-question survey based on the System Usability Scale (SUS).