Predicting falls based on a 2-minute walk test
Falls are the leading cause of injuries in older adults. Identifying older adults with risk for falls prior to discharge home from the Emergency Department (ED) could help direct fall prevention interventions, yet ED-based tools to assist risk stratification are under-developed. The aim of this study was to compare the performance of our proposed machine learning algorithms with existing screening tools to predict future falls in the 90-days post ED discharge for 150 older adults aged 65 years and older.
View Full Project DescriptionErvin Sejdic
VHA Home Healthcare
Engineering
Health and Related Sciences & Technology
University of Toronto
Accelerate