Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2023 May-Jun;13(3):e1492.
doi: 10.1002/widm.1492. Epub 2023 Feb 19.

Ethical issues when using digital biomarkers and artificial intelligence for the early detection of dementia

Elizabeth Ford  1 , Richard Milne  2   3 , Keegan Curlewis  4
Affiliations
Review

Ethical issues when using digital biomarkers and artificial intelligence for the early detection of dementia

Elizabeth Ford et al. Wiley Interdiscip Rev Data Min Knowl Discov. 2023 May-Jun.

Abstract

Dementia poses a growing challenge for health services but remains stigmatized and under-recognized. Digital technologies to aid the earlier detection of dementia are approaching market. These include traditional cognitive screening tools presented on mobile devices, smartphone native applications, passive data collection from wearable, in-home and in-car sensors, as well as machine learning techniques applied to clinic and imaging data. It has been suggested that earlier detection and diagnosis may help patients plan for their future, achieve a better quality of life, and access clinical trials and possible future disease modifying treatments. In this review, we explore whether digital tools for the early detection of dementia can or should be deployed, by assessing them against the principles of ethical screening programs. We conclude that while the importance of dementia as a health problem is unquestionable, significant challenges remain. There is no available treatment which improves the prognosis of diagnosed disease. Progression from early-stage disease to dementia is neither given nor currently predictable. Available technologies are generally not both minimally invasive and highly accurate. Digital deployment risks exacerbating health inequalities due to biased training data and inequity in digital access. Finally, the acceptability of early dementia detection is not established, and resources would be needed to ensure follow-up and support for those flagged by any new system. We conclude that early dementia detection deployed at scale via digital technologies does not meet standards for a screening program and we offer recommendations for moving toward an ethical mode of implementation. This article is categorized under:Application Areas > Health CareCommercial, Legal, and Ethical Issues > Ethical ConsiderationsTechnologies > Artificial Intelligence.

Keywords: artificial intelligence; dementia; digital biomarkers; early detection; ethics.

PubMed Disclaimer

Conflict of interest statement

The authors have declared no conflicts of interest for this article.

Figures

FIGURE 1
FIGURE 1
The continuum of Alzheimer's disease, where the preclinical phase may last for up to 20 years. Source: Adapted from Laver et al. (2016) and Gale et al. (2018).
FIGURE 2
FIGURE 2
Diagram showing how opportunities for intervention intersect with possibilities for detecting dementia. Source: Adapted from Dubois et al. (2016).
See this image and copyright information in PMC

References

FURTHER READING

    1. Dashwood, M. , Churchhouse, G. , Young, M. , & Kuruvilla, T. (2021). Artificial intelligence as an aid to diagnosing dementia: An overview. Progress in Neurology and Psychiatry, 25(3), 42–47.
    1. Dorsey, E. R. , Papapetropoulos, S. , Xiong, M. , & Kieburtz, K. (2017). The first frontier: Digital biomarkers for neurodegenerative disorders. Digital Biomarkers, 1(1), 6–13. - PMC - PubMed
    1. Ienca, M. , Vayena, E. , & Blasimme, A. (2018). Big data and dementia: Charting the route ahead for research, ethics, and policy. Frontiers in Medicine, 5, 13. - PMC - PubMed
    1. Weatherby, T. J. M. , & Agius, M. (2018). Ethical and organisational considerations in screening for dementia. Psychiatria Danubina, 30(Suppl 7), 463–468. - PubMed
    1. Wilson, J. M. G. , & Jungner, G. (1968). Principles and practice of screening for disease . http://apps.who.int/iris/bitstream/handle/10665/37650/WHO_PHP_34.pdf?seq...

References

    1. Abowd, G. D. , Bobick, A. F. , Essa, I. A. , Mynatt, E. D. , & Rogers, W. A. (2002). The aware home: A living laboratory for technologies for successful aging. Paper presented at the Proceedings of the AAAI‐02 Workshop “Automation as Caregiver”.
    1. Ackley, S. F. , Zimmerman, S. C. , Brenowitz, W. D. , Tchetgen, E. J. T. , Gold, A. L. , Manly, J. J. , Mayeda, E. R. , Filshtein, T. J. , Power, M. C. , Elahi, F. M. , & Brickman, A. M. (2021). Effect of reductions in amyloid levels on cognitive change in randomized trials: Instrumental variable meta‐analysis. BMJ, 372, n159. - PMC - PubMed
    1. Ada Lovelace Institute , & The Health Foundation . (2021). The data divide: Public attitudes to tackling social and health inequalities in the COVID‐19 pandemic and beyond . https://www.adalovelaceinstitute.org/wp-content/uploads/2021/03/The-data...
    1. Ahmed, M. R. , Zhang, Y. , Feng, Z. , Lo, B. , Inan, O. T. , & Liao, H. (2019). Neuroimaging and machine learning for dementia diagnosis: Recent advancements and future prospects. IEEE Reviews in Biomedical Engineering, 12, 19–33. 10.1109/RBME.2018.2886237 - DOI - PubMed
    1. Aisen, P. S. , Jimenez‐Maggiora, G. A. , Rafii, M. S. , Walter, S. , & Raman, R. (2022). Early‐stage Alzheimer disease: Getting trial‐ready. Nature Reviews Neurology, 18, 389–399. - PMC - PubMed

LinkOut - more resources