Photography in dermatology ‐ a scoping review: Practices, skin of color, patient preferences, and medical‐legal considerations

Kashetsky, Nadia; Mar, Kristie; Liu, Chaocheng; Rivers, Jason K.; Mukovozov, Ilya

doi:10.1111/ddg.15129

Cited by 1 publication

(1 citation statement)

References 39 publications

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“…Capturing images on darker skin tones differs from photographing light skin tones due to overexposure on SOC, resulting in unwanted flash reflections. 43,44 While there are techniques to avoid overexposure, 22 to our knowledge, there are no studies to determine the proficiency of dermatologists in photographing SOC using these techniques. This is important to assess, as practitioners may have inexperience in taking images of patients with SOC, resulting in images not being properly exposed.…”

Section: Image Standardizationmentioning

confidence: 99%

Artificial intelligence in dermatology: advancements and challenges in skin of color

Fliorent,

Fardman,

Podwojniak

et al. 2024

Int J Dermatology

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Artificial intelligence (AI) uses algorithms and large language models in computers to simulate human‐like problem‐solving and decision‐making. AI programs have recently acquired widespread popularity in the field of dermatology through the application of online tools in the assessment, diagnosis, and treatment of skin conditions. A literature review was conducted using PubMed and Google Scholar analyzing recent literature (from the last 10 years through October 2023) to evaluate current AI programs in use for dermatologic purposes, identifying challenges in this technology when applied to skin of color (SOC), and proposing future steps to enhance the role of AI in dermatologic practice. Challenges surrounding AI and its application to SOC stem from the underrepresentation of SOC in datasets and issues with image quality and standardization. With these existing issues, current AI programs inevitably do worse at identifying lesions in SOC. Additionally, only 30% of the programs identified in this review had data reported on their use in dermatology, specifically in SOC. Significant development of these applications is required for the accurate depiction of darker skin tone images in datasets. More research is warranted in the future to better understand the efficacy of AI in aiding diagnosis and treatment options for SOC patients.

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Section: Image Standardizationmentioning

confidence: 99%