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

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

Abstract 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) i...

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Autores principales: Michael R. Moore, Isabel D. Friesner, Emanuelle M. Rizk, Benjamin T. Fullerton, Manas Mondal, Megan H. Trager, Karen Mendelson, Ijeuru Chikeka, Tahsin Kurc, Rajarsi Gupta, Bethany R. Rohr, Eric J. Robinson, Balazs Acs, Rui Chang, Harriet Kluger, Bret Taback, Larisa J. Geskin, Basil Horst, Kevin Gardner, George Niedt, Julide T. Celebi, Robyn D. Gartrell-Corrado, Jane Messina, Tammie Ferringer, David L. Rimm, Joel Saltz, Jing Wang, Rami Vanguri, Yvonne M. Saenger
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
Materias:
Medicine
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Science
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Acceso en línea:https://doaj.org/article/8d415bf272d94264979172564903d21c
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https://doaj.org/article/8d415bf272d94264979172564903d21c

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