Your browser doesn't support javascript.
loading
A survey of skin tone assessment in prospective research.
Weir, Vanessa R; Dempsey, Katelyn; Gichoya, Judy Wawira; Rotemberg, Veronica; Wong, An-Kwok Ian.
Afiliação
  • Weir VR; Dermatology Service, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Dempsey K; Department of Medicine, Division of Pulmonary, Allergy, and Critical Care Medicine, Duke University, Durham, NC, USA.
  • Gichoya JW; Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, USA.
  • Rotemberg V; Dermatology Service, Memorial Sloan Kettering Cancer Center, New York, NY, USA. rotembev@mskcc.org.
  • Wong AI; Department of Medicine, Division of Pulmonary, Allergy, and Critical Care Medicine, Duke University, Durham, NC, USA. a.ian.wong@duke.edu.
NPJ Digit Med ; 7(1): 191, 2024 Jul 17.
Article em En | MEDLINE | ID: mdl-39014060
ABSTRACT
Increasing evidence supports reduced accuracy of noninvasive assessment tools, such as pulse oximetry, temperature probes, and AI skin diagnosis benchmarks, in patients with darker skin tones. The FDA is exploring potential strategies for device regulation to improve performance across diverse skin tones by including skin tone criteria. However, there is no consensus about how prospective studies should perform skin tone assessment in order to take this bias into account. There are several tools available to conduct skin tone assessments including administered visual scales (e.g., Fitzpatrick Skin Type, Pantone, Monk Skin Tone) and color measurement tools (e.g., reflectance colorimeters, reflectance spectrophotometers, cameras), although none are consistently used or validated across multiple medical domains. Accurate and consistent skin tone measurement depends on many factors including standardized environments, lighting, body parts assessed, patient conditions, and choice of skin tone assessment tool(s). As race and ethnicity are inadequate proxies for skin tone, these considerations can be helpful in standardizing the effect of skin tone on studies such as AI dermatology diagnoses, pulse oximetry, and temporal thermometers. Skin tone bias in medical devices is likely due to systemic factors that lead to inadequate validation across diverse skin tones. There is an opportunity for researchers to use skin tone assessment methods with standardized considerations in prospective studies of noninvasive tools that may be affected by skin tone. We propose considerations that researchers must take in order to improve device robustness to skin tone bias.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article