ArticleLasers in medical science2020
Correlation between light absorbance and skin color using fabricated skin phantoms with different colors.
Article in Lasers in medical science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed, 8 citations in OpenAlex.
- Subdermal Insertable Sensors for Health Monitoring: Applications, Challenges, and Emerging Technologies.Annals of biomedical engineering · 2026Review
- Optimizing tissue clearing methods for improved imaging of whole-mount retinas and optic nerves.Journal of neuroscience methods · 2025Article
- Human Skin Models in Biophotonics: Materials, Methods, and Applications.Advanced healthcare materials · 2025Review
- A survey of skin tone assessment in prospective research.NPJ digital medicine · 2024Review
- Assessment of ultraviolet and infrared radiation transmission through automobile windshields and side windows.Frontiers in public health · 2024Article
- Effect of Skin Type on Efficacy of Laser Treatment for Androgenetic Alopecia: A Review of the Literature.Skin appendage disorders · 2023Review
- Designing a Band for Vehicles' Drivers Induced by Ultraviolet and Infrared Radiations.Dermatology research and practice · 2022Article
- EGFRI-associated health-related quality of life by severity of skin toxicity in metastatic colorectal cancer patients receiving epidermal growth factor receptor inhibitor target therapy.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2020Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
The objective of this study is to investigate the need for detailed classification of skin colors through the quantification of skin color and light absorbance differences. Skin color is one of the most important factors in dermatological laser treatments. Dermatological laser treatments are currently performed based on the experience and judgment of the doctor with the Fitzpatrick scale. However, the Fitzpatrick scale and the doctor's experience were not quantified assessment methods for skin color classification and laser parameters selection. Improper selection of laser irradiating parameters can lead to undesirable tissue effects and treatment outcomes. We analyzed the correlations between absorbance and quantified colors using skin phantoms to identify that using the Fitzpatrick scale in dermatological treatments have limitations. Absorbance differences for different skin colors are measured at 532 nm with a custom-built system for radiant power measurements using skin phantoms fabricated with nine different colors. Some correlations between the color and absorbance agree with the Fitzpatrick scale. Generally, absorbance for the bright colored phantoms is lower than that for the darker colored phantoms. However, some phantoms fabricated with bright colors exceptionally have higher absorbance than those with darker colors. This means that for conventional standards, the Fitzpatrick scale may not always be accurate at 532-nm lights. Through these experiments, we demonstrate the need for a reliable classification standard for skin colors based on quantification of the skin colors and absorbance differences for each skin color as an alternative to the Fitzpatrick scale, which has limitations at certain wavelengths.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.