Investigation of the use of wearable data for cancer-specific mortality prediction in older adults

Daniel Kelly, Joan Condell, Salvatore Tedesco, Martina Andrulli, Marus Akerlund, Antti Alamäki, John Barton, Anna Nordstrom

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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 in order 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 AUC-ROC of 0.882, it is also highlighted that a feature subset which was only including demographics, a questionnaire, 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 proved its possible use in the accurate prediction of 2-7 year cancer-related mortality in older adults.
Original languageEnglish
Title of host publication43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Publication statusAccepted/In press - 15 Jul 2021
Event43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Virtual
Duration: 31 Oct 20214 Nov 2021

Conference

Conference43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Period31/10/214/11/21

Keywords

  • Cancer
  • Electronic Health Records
  • Mortality
  • Older Adults
  • Predictions
  • Wearables

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