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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Bibliographic Details
Main Authors: 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
Format: Article
Language:English
Published: Nature Publishing Group 2021-02-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-021-82305-1

Internet

https://doi.org/10.1038/s41598-021-82305-1

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