Fall Determinants in Older Adults
Document Type
Conference Presentation
Department
Health, Exercise, and Sport Sciences Department
Conference Title
IEEE World AI IoT Congress
Organization
Institute of Electrical and Electronics Engineers
Location
Seattle, WA
Date of Presentation
7-1-2023
DOI
10.1109/AIIoT58121.2023.10174548
First Page
184
Last Page
190
Abstract
Older adults commonly require special care and falling is a major reason for hospital admission. Identifying the cause of falls would help enable precautionary measures to be taken, which may reduce both injury and medical expenses. This study focuses on understanding underlying medical conditions or medicines associated with an increased risk of falls. Two datasets, one with trauma patient details and the other with fall-related admitted patient details, were analyzed to determine whether any relationship exists between falls and any underlying medical conditions and associated medications. Data visualization techniques and machine learning algorithms (e.g., SVC, Logistic Regression, and Naïve Bayes) have been used to study the cause of falls and whether they can be anticipated prior to their occurrence.
Recommended Citation
Banerjee, J.,
Gao, J.,
Saxe, J. M.,
Jacobson, L. E.,
&
Jensen, C. D.
(2023).
Fall Determinants in Older Adults.
Paper presented at IEEE World AI IoT Congress in Seattle, WA.
https://scholarlycommons.pacific.edu/cop-facpres/1569
