Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Hatzimemos A"'
Autor:
Kim, Randie H., Nomikou, Sofia, Coudray, Nicolas, Jour, George, Dawood, Zarmeena, Hong, Runyu, Esteva, Eduardo, Sakellaropoulos, Theodore, Donnelly, Douglas, Moran, Una, Hatzimemos, Aristides, Weber, Jeffrey S., Razavian, Narges, Aifantis, Iannis, Fenyo, David, Snuderl, Matija, Shapiro, Richard, Berman, Russell S., Osman, Iman, Tsirigos, Aristotelis
Publikováno v:
In Journal of Investigative Dermatology June 2022 142(6):1650-1658
Publikováno v:
Journal of Patient Experience, Vol 9 (2022)
Over the years, family-centered care in the field of pediatrics has become more prevalent and has improved the patient experience. Recent innovations within electronic health records (EHR), such as patient portals, have provided a more “patient-cen
Externí odkaz:
https://doaj.org/article/30b4457857154834bb0debe512e4ad44
Akademický článek
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Autor:
Diana Ximena Nichols‐Vinueza, Allyson Mateja, Aristides Hatzimemos, Madeline Michael, Marjohn Rasooly, Caeden Dempsey, Alaina Magnani, Erica Brittain, Alison M. Boyce, Pamela A. Frischmeyer‐Guerrerio
Publikováno v:
Allergy.
Autor:
Jeffrey S. Weber, Eduardo Esteva, Zarmeena Dawood, Iannis Aifantis, Aristotelis Tsirigos, George Jour, Matija Snuderl, Randie H Kim, Iman Osman, Sofia Nomikou, Nicolas Coudray, David Fenyö, Narges Razavian, Runyu Hong, Aristides Hatzimemos, Russell S. Berman, Richard L. Shapiro, Una Moran, Douglas Donnelly, Theodore Sakellaropoulos
Publikováno v:
J Invest Dermatol
Image-based analysis as a method for mutation detection can be advantageous in settings when tumor tissue is limited or unavailable for direct testing. In this study, we utilize two distinct and complementary machine-learning methods of analyzing who
Autor:
Richard L. Shapiro, Zarmeena Dawood, Theodore Sakellaropoulos, Matija Snuderl, Hatzimemos A, Iman Osman, Sofia Nomikou, Douglas Donnelly, Nicolas Coudray, Eduardo Esteva, Narges Razavian, George Jour, Runyu Hong, Una Moran, Russell S. Berman, Jeffrey S. Weber, Ioannis Aifantis, David Fenyö, Aristotelis Tsirigos, Kim Rh
Image-based analysis as a rapid method for mutation detection can be advantageous in research or clinical settings when tumor tissue is limited or unavailable for direct testing. Here, we applied a deep convolutional neural network (CNN) to whole sli
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d6f3c81300aaf981e9b2b1ad691e2f58
Publikováno v:
Journal of Investigative Dermatology. 140:S41
Publikováno v:
Journal of Patient Experience; 4/6/2022, Vol. 9, p1-3, 3p
Publikováno v:
In Journal of Investigative Dermatology July 2020 140(7) Supplement:S41-S41
Publikováno v:
In Journal of the American Academy of Dermatology 2005 52(6):1077-1081