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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Detalles Bibliográficos
Autores principales: 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: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7854647/
https://www.ncbi.nlm.nih.gov/pubmed/33531581
http://dx.doi.org/10.1038/s41598-021-82305-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7854647/
https://www.ncbi.nlm.nih.gov/pubmed/33531581
http://dx.doi.org/10.1038/s41598-021-82305-1

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