The poor performance of apps assessing skin cancer risk
A partir d'une revue systématique de la littérature publiée jusqu'en avril 2019 (9 études), cette étude analyse la précision des algorithmes des applications pour smartphone destinées à détecter un cancer de la peau à partir de l'image de la lésion suspecte
These apps are the product of inadequate evaluation and regulationOver the past year, technology companies have made headlines claiming that their artificially intelligent (AI) products can outperform clinicians at diagnosing breast cancer,1 brain tumours,2 and diabetic retinopathy.3 Claims such as these have influenced policy makers, and AI now forms a key component of the national health strategies in England, the United States, and China.It is positive to see healthcare systems embracing data analytics and machine learning. However, there are reasonable concerns about the efficacy, ethics, and safety of some commercial, AI health solutions.45 Trust in AI applications (or apps) heavily relies on the myth of the objective and omniscient algorithm, and our systems for generating and implementing evidence have not yet met the new specific challenges of AI. They may even have failed on the basics. In a linked article, Freeman and colleagues6 (doi:10.1136/bmj.m127) throw these general concerns into stark relief with a close examination of the evidence on diagnostic apps for skin cancer. The authors report results from a systematic review of studies evaluating the accuracy …
BMJ , éditorial en libre accès, 2019