Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

AI-based smartphone apps for risk assessment of skin cancer need more evaluation and better regulation


Smartphone applications (“apps”) with artificial intelligence (AI) algorithms are increasingly used in healthcare. Widespread adoption of these apps must be supported by a robust evidence-base and app manufacturers’ claims appropriately regulated. Current CE marking assessment processes inadequately protect the public against the risks created by using smartphone diagnostic apps.

This is a preview of subscription content, access via your institution

Access options

Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.


  1. Ferrante di Ruffano, L., Takwoingi, Y., Dinnes, J., Chuchu, N., Bayliss, S.E., Davenport, C. et al. Computer-assisted diagnosis techniques (dermoscopy and spectroscopy-based) for diagnosing skin cancer in adults. Cochrane Database Syst. Rev. 12, CD013186 (2019).

    Google Scholar 

  2. Ipsos-MORI. Technology tracker Q3. (2018).

  3. Flaten, H. K., St Claire, C., Schlager, E., Dunnick, C. A. & Dellavalle R. P. Growth of mobile applications in dermatology—2017 update. Dermatol Online J. 24, 13030/qt3hs7n9z6 (2018)

  4. Freeman, K., Dinnes, J., Chuchu, N., Takwoingi, Y., Bayliss, S.E., Matin, R.N. et al. Algorithm based smartphone apps to assess risk of skin cancer in adults: systematic review of diagnostic accuracy studies. BMJ 368, m127 (2020).

    Article  Google Scholar 

  5. Udrea, A., Mitra, G.D., Costea, D., Noels, E.C., Wakkee, M., Siegel, D.M. et al. Accuracy of a smartphone application for triage of skin lesions based on machine learning algorithms. J. Eur. Acad. Dermatol. Venereol. 34, 648–655 (2020).

    Article  CAS  Google Scholar 

  6. Deeks, J. J., Dinnes, J. & Williams, H. C. Sensitivity and specificity of SkinVision are likely to have been overestimated. J. Eur. Acad. Dermatol. Venereol. 34, e582–e583 (2020).

    Article  CAS  Google Scholar 

  7. Cancer Research UK. Non-melanoma skin cancer incidence statistics (2016).

  8. FDA. Mobile medical applications—guidance for industry and food and drug administration staff (Food and Drug Administration, Rockville MD, 2015).

  9. Singh, K., Drouin, K., Newmark, L.P., Lee, J., Faxvaag, A., Rozenblum, R. et al. Many mobile health apps target high-need, high-cost populations, but gaps remain. Health Aff. (Millwood) 35, 2310–2318 (2016).

    Article  Google Scholar 

  10. Torous, J. B., Chan, S.R., Gipson, S.Y.M.T., Kim, J.W., Nguyen, T.Q., Luo, J. et al. A hierarchical framework for evaluation and informed decision making regarding smartphone apps for clinical care. Psychiatr. Serv. 69, 498–500 (2018).

    Article  Google Scholar 

Download references


We would like to thank Prof. Jonathan Deeks and Prof. Hywel Williams for comments on an earlier version of the manuscript.

Author information

Authors and Affiliations



R.M. and J.D. contributed equally to this work. Both authors contributed to the conception of the work, drafted the manuscript and approved the final version. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.

Corresponding author

Correspondence to Jacqueline Dinnes.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent to publish

Not applicable.

Data availability

Not applicable.

Competing interests

The authors declare no competing interests.

Funding information

J.D. is supported by the National Institute for Health Research (NIHR) Birmingham Biomedical Research Centre at the University Hospitals Birmingham NHS Foundation Trust and the University of Birmingham (grant reference No BRC-1215-20009). The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Matin, R.N., Dinnes, J. AI-based smartphone apps for risk assessment of skin cancer need more evaluation and better regulation. Br J Cancer 124, 1749–1750 (2021).

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:


Quick links