Impact of Medical History on Technology Adoption in Utah Population Database

摘要

In this paper we study the use of medical history information extracted from the Utah Population Database (UPDB) to predict adoption of a reminder solution for people with dementia. The adoption model was built using 24 categorised features. The kNN classification algorithm gave the best performance with 85.8 % accuracy. Whilst data from the UPDB is more readily available than that in our previous work, the results highlight the benefit of including psychosocial and background information within an adoption model.