A deep learning algorithm with high sensitivity for the detection of basal cell carcinoma in Mohs micrographic surgery frozen sections - 12/10/21
Doi : 10.1016/j.jaad.2020.09.012
Gabriele Campanella, MS a, b, Kishwer S. Nehal, MD c, Erica H. Lee, MD c, Anthony Rossi, MD c, Brandon Possum, HT c, Genna Manuel, HT c, Thomas J. Fuchs, PhD a, b, Klaus J. Busam, MD b, ⁎ 
a Weill Cornell Graduate School of Medical Sciences, New York, New York
b Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York
c Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York
∗Correspondence to: Klaus J. Busam, MD, Department of Pathology, Rm C530, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065Department of PathologyRm C530Memorial Sloan Kettering Cancer Center1275 York AveNew YorkNY10065
| Funding: Supported in part by the Cancer Center Support Grant of National Institutes of Health/National Cancer Institute grant P30CA008748. |
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| Conflicts of interest: Dr Fuchs owns equity of PAIGE.AI. All other authors have no conflicts of interest to declare. |
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| IRB status: Approved. |
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| Reprints not available from the authors. |
© 2020
American Academy of Dermatology, Inc.. Pubblicato da Elsevier Masson SAS. Tutti i diritti riservati.
Vol 85 - N° 5
P. 1285-1286 - novembre 2021 Ritorno al numero
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