An open source automated tumor infiltrating lymphocyte algorithm for prognosis in melanoma

Histology data exists for many cancer samples and the ability to automatically image this data may provide prognostic information. Here, the authors generated an algorithm to measure tumour infiltrating lymphocytes in melanoma histology specimens and show that the ratio of these immune cells to tumo...

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Autores principales:	Balazs Acs, Fahad Shabbir Ahmed, Swati Gupta, Pok Fai Wong, Robyn D. Gartrell, Jaya Sarin Pradhan, Emanuelle M. Rizk, Bonnie Gould Rothberg, Yvonne M. Saenger, David L. Rimm
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2019
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/aa7ab2f3684448649179b824d976a4d8
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spelling	oai:doaj.org-article:aa7ab2f3684448649179b824d976a4d82021-12-02T17:01:26ZAn open source automated tumor infiltrating lymphocyte algorithm for prognosis in melanoma10.1038/s41467-019-13043-22041-1723https://doaj.org/article/aa7ab2f3684448649179b824d976a4d82019-11-01T00:00:00Zhttps://doi.org/10.1038/s41467-019-13043-2https://doaj.org/toc/2041-1723Histology data exists for many cancer samples and the ability to automatically image this data may provide prognostic information. Here, the authors generated an algorithm to measure tumour infiltrating lymphocytes in melanoma histology specimens and show that the ratio of these immune cells to tumour cells has prognostic value.Balazs AcsFahad Shabbir AhmedSwati GuptaPok Fai WongRobyn D. GartrellJaya Sarin PradhanEmanuelle M. RizkBonnie Gould RothbergYvonne M. SaengerDavid L. RimmNature PortfolioarticleScienceQENNature Communications, Vol 10, Iss 1, Pp 1-7 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Balazs Acs Fahad Shabbir Ahmed Swati Gupta Pok Fai Wong Robyn D. Gartrell Jaya Sarin Pradhan Emanuelle M. Rizk Bonnie Gould Rothberg Yvonne M. Saenger David L. Rimm An open source automated tumor infiltrating lymphocyte algorithm for prognosis in melanoma
description	Histology data exists for many cancer samples and the ability to automatically image this data may provide prognostic information. Here, the authors generated an algorithm to measure tumour infiltrating lymphocytes in melanoma histology specimens and show that the ratio of these immune cells to tumour cells has prognostic value.
format	article
author	Balazs Acs Fahad Shabbir Ahmed Swati Gupta Pok Fai Wong Robyn D. Gartrell Jaya Sarin Pradhan Emanuelle M. Rizk Bonnie Gould Rothberg Yvonne M. Saenger David L. Rimm
author_facet	Balazs Acs Fahad Shabbir Ahmed Swati Gupta Pok Fai Wong Robyn D. Gartrell Jaya Sarin Pradhan Emanuelle M. Rizk Bonnie Gould Rothberg Yvonne M. Saenger David L. Rimm
author_sort	Balazs Acs
title	An open source automated tumor infiltrating lymphocyte algorithm for prognosis in melanoma
title_short	An open source automated tumor infiltrating lymphocyte algorithm for prognosis in melanoma
title_full	An open source automated tumor infiltrating lymphocyte algorithm for prognosis in melanoma
title_fullStr	An open source automated tumor infiltrating lymphocyte algorithm for prognosis in melanoma
title_full_unstemmed	An open source automated tumor infiltrating lymphocyte algorithm for prognosis in melanoma
title_sort	open source automated tumor infiltrating lymphocyte algorithm for prognosis in melanoma
publisher	Nature Portfolio
publishDate	2019
url	https://doaj.org/article/aa7ab2f3684448649179b824d976a4d8
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An open source automated tumor infiltrating lymphocyte algorithm for prognosis in melanoma

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