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Τετάρτη 29 Σεπτεμβρίου 2021

The potential of using artificial intelligence to improve skin cancer diagnoses in Hawai‘i’s multiethnic population

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Skin cancer remains the most commonly diagnosed cancer in the USA with more than 1 million new cases each year. Melanomas account for about 1% of all skin cancers and most skin cancer deaths. Multiethnic individuals whose skin is pigmented underestimate their risk for skin cancers and melanomas and may delay seeking a diagnosis. The use of artificial intelligence may help improve the diagnostic precision of dermatologists/physicians to identify malignant lesions. To validate our artificial intelligence's efficiency in distinguishing between images, we utilized 50 images obtained from our International Skin Imaging Collaboration dataset (n = 25) and pathologically confirmed lesions (n = 25). We compared the ability of our artificial intelligence to visually diagnose these 50 skin cancer lesions with a panel of three dermatologists. The artificial intelligence model better differentiated between melanoma vs. nonmelanoma with an area under the curve of 0.948. The three-panel member dermatologists correctly diagnosed a similar number of images (n = 35) as the artificial intelligence program (n = 34). Fleiss' kappa (ĸ) score for the raters and artificial intelligence indicated fair (0.247) agreement. However, the combined result of the dermatologists panel with the artificial i ntelligence assessments correctly identified 100% of the images from the test data set. Our artificial intelligence platform was able to utilize visual images to discriminate melanoma from nonmelanoma, using de-identified images. The combined results of the artificial intelligence with those of the dermatologists support the use of artificial intelligence as an efficient lesion assessment strategy to reduce time and expense in diagnoses to reduce delays in treatment. Received 1 March 2021 Accepted 6 August 2021 Correspondence to Mark Lee Willingham Jr., MS, Department of Sociology, Community Health Educator, University of Hawai'i Cancer Center, 701 Ilalo St., Suite #414, Honolulu, HI 96813, Hawai'i, USA, Tel: 1 808 441 8186; fax: 1 808 586 3052; e-mail: Mlw237@hawaii.edu Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.
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