Ontology highlight
ABSTRACT:
SUBMITTER: Moore MR
PROVIDER: S-EPMC7854647 | biostudies-literature | 2021 Feb
REPOSITORIES: biostudies-literature
Moore Michael R MR Friesner Isabel D ID Rizk Emanuelle M EM Fullerton Benjamin T BT Mondal Manas M Trager Megan H MH Mendelson Karen K Chikeka Ijeuru I Kurc Tahsin T Gupta Rajarsi R Rohr Bethany R BR Robinson Eric J EJ Acs Balazs B Chang Rui R Kluger Harriet H Taback Bret B Geskin Larisa J LJ Horst Basil B Gardner Kevin K Niedt George G Celebi Julide T JT Gartrell-Corrado Robyn D RD Messina Jane J Ferringer Tammie T Rimm David L DL Saltz Joel J Wang Jing J Vanguri Rami R Saenger Yvonne M YM
Scientific reports 20210202 1
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 early-stage melanomas. We tested whether automated digital (TIL) analysis (ADTA) improved accuracy of prediction of disease specific survival (DSS) based on current pathology standards. ADTA was applied t ...[more]