{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T14:53:48Z","timestamp":1790780028865,"version":"4.1.0"},"reference-count":43,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2021,12,29]],"date-time":"2021-12-29T00:00:00Z","timestamp":1640736000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>The diagnosis and treatment of non-melanoma skin cancer remain urgent problems. Histological examination of biopsy material\u2014the gold standard of diagnosis\u2014is an invasive procedure that requires a certain amount of time to perform. The ability to detect abnormal cells using fluorescence spectroscopy (FS) has been shown in many studies. This technique is rapidly expanding due to its safety, relative cost-effectiveness, and efficiency. However, skin lesion FS-based diagnosis is challenging due to a number of single overlapping spectra emitted by fluorescent molecules, making it difficult to distinguish changes in the overall spectrum and the molecular basis for it. We applied deep learning (DL) algorithms to quantitatively assess the ability of FS to differentiate between pathologies and normal skin. A total of 137 patients with various forms of primary and recurrent basal cell carcinoma (BCC) were observed by a multispectral laser-based device with a built-in neural network (NN) \u201cDSL-1\u201d. We measured the fluorescence spectra of suspected non-melanoma skin cancers and compared them with \u201cnormal\u201d skin spectra. These spectra were input into DL algorithms to determine whether the skin is normal, pigmented normal, benign, or BCC. The preoperative differential AI-driven fluorescence diagnosis method correctly predicted the BCC lesions. We obtained an average sensitivity of 62% and average specificity of 83% in our experiments. Thus, the presented \u201cDSL-1\u201d diagnostic device can be a viable tool for the real-time diagnosis and guidance of non-melanoma skin cancer resection.<\/jats:p>","DOI":"10.3390\/diagnostics12010072","type":"journal-article","created":{"date-parts":[[2021,12,29]],"date-time":"2021-12-29T08:12:15Z","timestamp":1640765535000},"page":"72","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Preoperative AI-Driven Fluorescence Diagnosis of Non-Melanoma Skin Cancer"],"prefix":"10.3390","volume":"12","author":[{"given":"Victoriya","family":"Andreeva","sequence":"first","affiliation":[{"name":"Moscow Regional Research and Clinical Institute (MONIKI), 129110 Moscow, Russia"},{"name":"Dermclinic LLC, Bannyy Pereulok 2c2, 129110 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Evgeniia","family":"Aksamentova","sequence":"additional","affiliation":[{"name":"Moscow Regional Research and Clinical Institute (MONIKI), 129110 Moscow, Russia"},{"name":"Dermclinic LLC, Bannyy Pereulok 2c2, 129110 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrey","family":"Muhachev","sequence":"additional","affiliation":[{"name":"Deep Smart Light Ltd., 7 Bell Yard, London WC2A 2JR, UK"},{"name":"The Advanced Educational Scientific Center, Kolmogorov\u2019s Boarding School, Moscow State University (AESC MSU), 121357 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexey","family":"Solovey","sequence":"additional","affiliation":[{"name":"Deep Smart Light Ltd., 7 Bell Yard, London WC2A 2JR, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Igor","family":"Litvinov","sequence":"additional","affiliation":[{"name":"Deep Smart Light Ltd., 7 Bell Yard, London WC2A 2JR, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexey","family":"Gusarov","sequence":"additional","affiliation":[{"name":"Deep Smart Light Ltd., 7 Bell Yard, London WC2A 2JR, UK"},{"name":"Moscow Power Engineering Institute, National Research University, 111250 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Natalia N.","family":"Shevtsova","sequence":"additional","affiliation":[{"name":"Moscow Regional Research and Clinical Institute (MONIKI), 129110 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dmitry","family":"Kushkin","sequence":"additional","affiliation":[{"name":"Dermclinic LLC, Bannyy Pereulok 2c2, 129110 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1110-8589","authenticated-orcid":false,"given":"Karina","family":"Litvinova","sequence":"additional","affiliation":[{"name":"Department of Bioengineering, Imperial College London, South Kensington, London SW7 2BT, UK"},{"name":"Aston Medical School, College of Health & Life Sciences, Aston University, Aston Triangle, Birmingham B4 7ET, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"673","DOI":"10.1016\/S0140-6736(09)61196-X","article-title":"Non-melanoma skin cancer","volume":"375","author":"Madan","year":"2010","journal-title":"Lancet"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"553","DOI":"10.1016\/j.jaad.2011.04.004","article-title":"The risk of squamous cell and basal cell cancer associated with psoralen and ultraviolet A therapy: A 30-year prospective study","volume":"66","author":"Stern","year":"2012","journal-title":"J. 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