{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T21:07:06Z","timestamp":1773176826803,"version":"3.50.1"},"reference-count":41,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2025,7,13]],"date-time":"2025-07-13T00:00:00Z","timestamp":1752364800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Fox Chase Cancer Center and the Cancer Center","award":["P30CA006927"],"award-info":[{"award-number":["P30CA006927"]}]},{"name":"Temple University","award":["P30CA006927"],"award-info":[{"award-number":["P30CA006927"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>The absence of skin color information in skin cancer datasets poses a significant challenge for accurate diagnosis using artificial intelligence models, particularly for non-white populations. In this paper, based on the Monk Skin Tone (MST) scale, which is less biased than the Fitzpatrick scale, we propose MST-AI, a novel method for detecting skin color in images of large datasets, such as the International Skin Imaging Collaboration (ISIC) archive. The approach includes automatic frame, lesion removal, and lesion segmentation using convolutional neural networks, and modeling normal skin tones with a Variational Bayesian Gaussian Mixture Model (VB-GMM). The distribution of skin color predictions was compared with MST scale probability distribution functions (PDFs) using the Kullback-Leibler Divergence (KLD) metric. Validation against manual annotations and comparison with K-means clustering of image and skin mean RGBs demonstrated the superior performance of the MST-AI, with Kendall\u2019s Tau, Spearman\u2019s Rho, and Normalized Discounted Cumulative Gain (NDGC) of 0.68, 0.69, and 1.00, respectively. This research lays the groundwork for developing unbiased AI models for early skin cancer diagnosis by addressing skin color imbalances in large datasets.<\/jats:p>","DOI":"10.3390\/jimaging11070235","type":"journal-article","created":{"date-parts":[[2025,7,14]],"date-time":"2025-07-14T07:54:23Z","timestamp":1752479663000},"page":"235","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["MST-AI: Skin Color Estimation in Skin Cancer Datasets"],"prefix":"10.3390","volume":"11","author":[{"given":"Vahid","family":"Khalkhali","sequence":"first","affiliation":[{"name":"Electrical and Computer Engineering Department, Temple University, Philadelphia, PA 19122, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0571-3192","authenticated-orcid":false,"given":"Hayan","family":"Lee","sequence":"additional","affiliation":[{"name":"Cancer Epigenetics Institute, Nuclear Dynamics and Cancer Program, Fox Chase Cancer Center, Philadelphia, PA 19111, USA"},{"name":"Department of Medical Genetics and Molecular Biochemistry, Lewis Katz School of Medicine (LKSOM), Temple University Health System, Philadelphia, PA 19140, USA"},{"name":"Department of Cancer and Cellular Biology, Lewis Katz School of Medicine (LKSOM), Temple University Health System, Philadelphia, PA 19140, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-4572-3159","authenticated-orcid":false,"given":"Joseph","family":"Nguyen","sequence":"additional","affiliation":[{"name":"Cancer Epigenetics Institute, Nuclear Dynamics and Cancer Program, Fox Chase Cancer Center, Philadelphia, PA 19111, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-1057-736X","authenticated-orcid":false,"given":"Sergio","family":"Zamora-Erazo","sequence":"additional","affiliation":[{"name":"Cancer Epigenetics Institute, Nuclear Dynamics and Cancer Program, Fox Chase Cancer Center, Philadelphia, PA 19111, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0816-4942","authenticated-orcid":false,"given":"Camille","family":"Ragin","sequence":"additional","affiliation":[{"name":"Cancer Prevention and Control Program, Fox Chase Cancer Center, Philadelphia, PA 19111, USA"}]},{"given":"Abhishek","family":"Aphale","sequence":"additional","affiliation":[{"name":"Division of Dermatology, Melanoma and Skin Cancer Program, Fox Chase Cancer Center, Philadelphia, PA 19111, USA"}]},{"given":"Alfonso","family":"Bellacosa","sequence":"additional","affiliation":[{"name":"Cancer Epigenetics Institute, Nuclear Dynamics and Cancer Program, Fox Chase Cancer Center, Philadelphia, PA 19111, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3124-0990","authenticated-orcid":false,"given":"Ellis P.","family":"Monk","sequence":"additional","affiliation":[{"name":"Department of Sociology, Harvard University, Cambridge, MA 02138, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5464-1773","authenticated-orcid":false,"given":"Saroj K.","family":"Biswas","sequence":"additional","affiliation":[{"name":"Electrical and Computer Engineering Department, Temple University, Philadelphia, PA 19122, USA"}]}],"member":"1968","published-online":{"date-parts":[[2025,7,13]]},"reference":[{"key":"ref_1","first-page":"591","article-title":"Vital Signs: Melanoma Incidence and Mortality Trends and Projections\u2014United States, 1982\u20132030","volume":"64","author":"Guy","year":"2015","journal-title":"MMWR Morb Mortal Wkly. 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