Abstract
It is well known that older adults are more prone to falls due to their cognitive decline with the ageing process. Falls and the consequences of falls can have a huge impact on older adults and their families. Communication of such risks must involve the individual, their families and health professionals. This paper explores the use of machine learning algorithms to pre-dict if multiple risk factors including falling can lead to recurrent falls based on the data collected by The Irish Longitudinal Study on Ageing. Initial results shows that certain risk factors do in fact contribute to older adults falling such as overall health, mental and long-term health as well as blackouts and joint replacements.
Original language | English |
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Title of host publication | 15th International Conference on Machine Learning and Data Mining |
Pages | 1-5 |
Number of pages | 5 |
Publication status | Published (in print/issue) - 12 Jul 2019 |
Event | 15th International Conference on Machine Learning and Data Mining - New York, United States Duration: 13 Jul 2019 → 18 Jul 2019 http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=78944©ownerid=83716 |
Conference
Conference | 15th International Conference on Machine Learning and Data Mining |
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Abbreviated title | MLDM 2019 |
Country/Territory | United States |
City | New York |
Period | 13/07/19 → 18/07/19 |
Internet address |
Keywords
- Falls
- Machine Learning
- Risk Factors