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Investigation of th...
Investigation of the analysis of wearable data for cancer-specific mortality prediction in older adults
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- Tedesco, Salvatore (författare)
- University College Cork, Tyndall National Institute, Cork, Ireland
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- Andrulli, Martina (författare)
- University College Cork, Tyndall National Institute, Cork, Ireland
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- Åkerlund Larsson, Markus (författare)
- Umeå universitet,Institutionen för folkhälsa och klinisk medicin
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- Kelly, Daniel (författare)
- School of Computing, Engineering and Intelligent Systems, Ulster University, Londonderry, United Kingdom
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- Timmons, Suzanne (författare)
- Centre for Gerontology and Rehabilitation, University College Cork, Cork, Ireland
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- Alamäki, Antti (författare)
- Department of Physiotherapy, Karelia University of Applied Sciences, Joensuu, Finland
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- Barton, John (författare)
- University College Cork, Tyndall National Institute, Cork, Ireland
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- Condell, Joan (författare)
- School of Computing, Engineering and Intelligent Systems, Ulster University, Londonderry, United Kingdom
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- O'Flynn, Brendan (författare)
- University College Cork, Tyndall National Institute, Cork, Ireland
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- Nordström, Anna (författare)
- Umeå universitet,Institutionen för folkhälsa och klinisk medicin,School of Sport Sciences, UiT The Arctic University of Norway, Tromsø, Norway
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(creator_code:org_t)
- IEEE, 2021
- 2021
- Engelska.
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Ingår i: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. - : IEEE. - 9781728111797 ; , s. 1848-1851
- Relaterad länk:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Cancer is an aggressive disease which imparts a tremendous socio-economic burden on the international community. Early detection is an important aspect in improving survival rates for cancer sufferers; however, very few studies have investigated the possibility of predicting which people have the highest risk to develop this disease, even years before the traditional symptoms first occur. In this paper, a dataset from a longitudinal study which was collected among 2291 70-year olds in Sweden has been analyzed to investigate the possibility for predicting 2-7 year cancer-specific mortality. A tailored ensemble model has been developed to tackle this highly imbalanced dataset. The performance with different feature subsets has been investigated to evaluate the impact that heterogeneous data sources may have on the overall model. While a full-features model shows an Area Under the ROC Curve (AUC-ROC) of 0.882, a feature subset which only includes demographics, self-report health and lifestyle data, and wearable dataset collected in free-living environments presents similar performance (AUC-ROC: 0.857). This analysis confirms the importance of wearable technology for providing unbiased health markers and suggests its possible use in the accurate prediction of 2-7 year cancer-related mortality in older adults.
Ämnesord
- MEDICIN OCH HÄLSOVETENSKAP -- Hälsovetenskap -- Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Health Sciences -- Public Health, Global Health, Social Medicine and Epidemiology (hsv//eng)
Nyckelord
- Cancer
- Electronic Health Records
- Mortality
- Older Adults
- Prediction
- Wearables
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
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