부산대학교 도서관

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.