Automated digital TIL analysis (ADTA) adds prognostic value to standard assessment of depth and ulceration in primary melanoma

Accurate prognostic biomarkers in early-stage melanoma are urgently needed to stratify patients for clinical trials of adjuvant therapy. We applied a previously developed open source deep learning algorithm to detect tumor-infiltrating lymphocytes (TILs) in hematoxylin and eosin (H&E) images of...

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Detalhes bibliográficos
Publicado no:Sci Rep
Main Authors: Moore, Michael R., Friesner, Isabel D., Rizk, Emanuelle M., Fullerton, Benjamin T., Mondal, Manas, Trager, Megan H., Mendelson, Karen, Chikeka, Ijeuru, Kurc, Tahsin, Gupta, Rajarsi, Rohr, Bethany R., Robinson, Eric J., Acs, Balazs, Chang, Rui, Kluger, Harriet, Taback, Bret, Geskin, Larisa J., Horst, Basil, Gardner, Kevin, Niedt, George, Celebi, Julide T., Gartrell-Corrado, Robyn D., Messina, Jane, Ferringer, Tammie, Rimm, David L., Saltz, Joel, Wang, Jing, Vanguri, Rami, Saenger, Yvonne M.
Formato: Artigo
Idioma:Inglês
Publicado em: Nature Publishing Group UK 2021
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Article
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC7854647/
https://ncbi.nlm.nih.gov/pubmed/33531581
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-021-82305-1
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