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Investigation of the analysis of wearable data for cancer-specific mortality prediction in older adults
University College Cork, Tyndall National Institute, Cork, Ireland.
University College Cork, Tyndall National Institute, Cork, Ireland.
Umeå universitet, Medicinska fakulteten, Institutionen för folkhälsa och klinisk medicin.
School of Computing, Engineering and Intelligent Systems, Ulster University, Londonderry, United Kingdom.
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2021 (Engelska)Ingår i: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, IEEE, 2021, s. 1848-1851Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

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.

Ort, förlag, år, upplaga, sidor
IEEE, 2021. s. 1848-1851
Serie
International Conference of the IEEE Engineering in Medicine and Biology Society, ISSN 1557-170X
Nyckelord [en]
Cancer, Electronic Health Records, Mortality, Older Adults, Prediction, Wearables
Nationell ämneskategori
Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi
Identifikatorer
URN: urn:nbn:se:umu:diva-202939DOI: 10.1109/EMBC46164.2021.9630370ISI: 000760910501198PubMedID: 34891647Scopus ID: 2-s2.0-85122501163ISBN: 9781728111797 (digital)OAI: oai:DiVA.org:umu-202939DiVA, id: diva2:1726985
Konferens
43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021, NOV 01-05, 2021, Online
Tillgänglig från: 2023-01-14 Skapad: 2023-01-14 Senast uppdaterad: 2023-01-14Bibliografiskt granskad

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Åkerlund Larsson, MarkusNordström, Anna

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Åkerlund Larsson, MarkusNordström, Anna
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Institutionen för folkhälsa och klinisk medicin
Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi

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