Applications of patient contributed data and artificial intelligence software in dermatology mobile apps

Scientific Abstract

Many dermatology mobile apps, especially those that utilize artificial intelligence (AI)/image recognition, would have limited applicability without user-contributed data. The keywords “acne” and “skin cancer” were searched in the Apple App Store in 2022 and representative apps utilizing AI/image recognition software were identified. We identified characteristics of included apps and potential areas of improvement.

Mobile dermatology apps leverage AI software to analyze user-contributed information in various different ways. Several acne apps analyze a patient’s image of their face to provide personalized acne regimens and skin care routines. Certain skin cancer apps provide users with a diagnosis and a percentage of how benign appearing a lesion is perceived to be.

While dermatology apps may be promising tools for the management of dermatologic conditions, they are associated with potential concerns. There is limited transparency regarding how the proprietary AI models of mobile apps are developed, prompting uncertainty in image analysis and user privacy. Further research should evaluate analytic capabilities, and apps should clearly state data security guidelines. Other challenges include equity and availability concerns, which may be alleviated by removing in-app transactions.

Overcoming these challenges can translate mobile apps into robust tools for the management of dermatologic conditions.

Lay Abstract

Many dermatology mobile apps, especially those that utilize artificial intelligence (AI)/image recognition, would have limited applicability without user-contributed data. Patients play an essential role in the functioning of dermatology mobile apps by uploading their photos to be analyzed by image recognition software. We identified several acne and skin cancer apps on the Apple App Store in 2022 and characterized their functional capabilities and limitations. While apps provide therapeutic recommendations and characterize whether a skin lesion is benign or malignant, they may be associated with varying potential limitations in areas including technology, privacy, equity, and availability. Overcoming these potential challenges can lead to the development of more robust dermatology apps to assist patients and medical providers with the management of skin conditions.

Clinical Implications

Patient-contributed data is critical for the development of dermatology-related apps, which can help improve the management of skin conditions. There is a significant disparity between the potential of AI in dermatology and the availability of reliable, transparent apps for patients.

Applications of patient contributed data and artificial intelligence software in dermatology mobile apps

Scientific Abstract

Lay Abstract

Clinical Implications

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