JAMA Dermatology

<jats:sec id="ab-dbr240004-4"><jats:title>Importance</jats:title><jats:p>With advancements in mobile technology and artificial intelligence (AI) methods, there has been a substantial surge in the availability of direct-to-consumer mobile applications (apps) claiming to aid in the assessment and management of diverse skin conditions. Despite widespread patient downloads, these apps exhibit limited evidence supporting their efficacy.</jats:p></jats:sec><jats:sec id="ab-dbr240004-5"><jats:title>Objective</jats:title><jats:p>To identify and characterize current English-language AI dermatology mobile apps available for download, focusing on aspects such as purpose, supporting evidence, regulatory status, clinician input, data privacy measures, and use of image data.</jats:p></jats:sec><jats:sec id="ab-dbr240004-6"><jats:title>Evidence Review</jats:title><jats:p>In this cross-sectional study, both Apple and Android mobile app stores were systematically searched for dermatology-related apps that use AI algorithms. Each app’s purpose, target audience, evidence-based claims, algorithm details, data availability, clinician input during development, and data usage privacy policies were evaluated.</jats:p></jats:sec><jats:sec id="ab-dbr240004-7"><jats:title>Findings</jats:title><jats:p>A total of 909 apps were initially identified. Following the removal of 518 duplicates, 391 apps remained. Subsequent review excluded 350 apps due to nonmedical nature, non-English languages, absence of AI features, or unavailability, ultimately leaving 41 apps for detailed analysis. The findings revealed several concerning aspects of the current landscape of AI apps in dermatology. Notably, none of the apps were approved by the US Food and Drug Administration, and only 2 of the apps included disclaimers for the lack of regulatory approval. Overall, the study found that these apps lack supporting evidence, input from clinicians and/or dermatologists, and transparency in algorithm development, data usage, and user privacy.</jats:p></jats:sec><jats:sec id="ab-dbr240004-8"><jats:title>Conclusions and Relevance</jats:title><jats:p>This cross-sectional study determined that although AI dermatology mobile apps hold promise for improving access to care and patient outcomes, in their current state, they may pose harm due to potential risks, lack of consistent validation, and misleading user communication. Addressing challenges in efficacy, safety, and transparency through effective regulation, validation, and standardized evaluation criteria is essential to harness the benefits of these apps while minimizing risks.</jats:p></jats:sec>

Mobile applications in dermatology.

JAMA Dermatol

Accuracy of commercially available smartphone applications for the detection of melanoma.

Br J Dermatol

Algorithm based smartphone apps to assess risk of skin cancer in adults: systematic review of diagnostic accuracy studies.

Artificial intelligence-based skin cancer phone apps unreliable.

JAMA

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

Br J Cancer

Smartphone applications for triaging adults with skin lesions that are suspicious for melanoma.

Cochrane Database Syst Rev

Multinational landscape of health app policy: toward regulatory consensus on digital health.

NPJ Digit Med

Health app policy: international comparison of nine countries’ approaches.

Comparison of humans versus mobile phone-powered artificial intelligence for the diagnosis and management of pigmented skin cancer in secondary care: a multicentre, prospective, diagnostic, clinical trial.

Lancet Digit Health

The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions.

Sci Data

Expanding personalized, data-driven dermatology: leveraging digital health technology and machine learning to improve patient outcomes.

JID Innov

Checklist for evaluation of image-based artificial intelligence reports in dermatology: CLEAR derm consensus guidelines from the international skin imaging collaboration artificial intelligence working group.

With advancements in mobile technology and artificial intelligence (AI) methods, there has been a substantial surge in the availability of direct-to-consumer mobile applications (apps) claiming to aid in the assessment and management of diverse skin conditions. Despite widespread patient downloads, these apps exhibit limited evidence supporting their efficacy.
To identify and characterize current English-language AI dermatology mobile apps available for download, focusing on aspects such as purpose, supporting evidence, regulatory status, clinician input, data privacy measures, and use of image data.
In this cross-sectional study, both Apple and Android mobile app stores were systematically searched for dermatology-related apps that use AI algorithms. Each app's purpose, target audience, evidence-based claims, algorithm details, data availability, clinician input during development, and data usage privacy policies were evaluated.
A total of 909 apps were initially identified. Following the removal of 518 duplicates, 391 apps remained. Subsequent review excluded 350 apps due to nonmedical nature, non-English languages, absence of AI features, or unavailability, ultimately leaving 41 apps for detailed analysis. The findings revealed several concerning aspects of the current landscape of AI apps in dermatology. Notably, none of the apps were approved by the US Food and Drug Administration, and only 2 of the apps included disclaimers for the lack of regulatory approval. Overall, the study found that these apps lack supporting evidence, input from clinicians and/or dermatologists, and transparency in algorithm development, data usage, and user privacy.
This cross-sectional study determined that although AI dermatology mobile apps hold promise for improving access to care and patient outcomes, in their current state, they may pose harm due to potential risks, lack of consistent validation, and misleading user communication. Addressing challenges in efficacy, safety, and transparency through effective regulation, validation, and standardized evaluation criteria is essential to harness the benefits of these apps while minimizing risks.

Current State of Dermatology Mobile Applications With Artificial Intelligence Features.

Current State of Dermatology Mobile Applications With Artificial Intelligence Features

Current State of Dermatology Mobile Applications With Artificial Intelligence Features

Clinical Summary

What was studied

Key findings

Study limitations

Clinical implications

Related Questions