Supplemental Material, sj-docx-1-tpx-10.1177_0192623320973986 - Using Deep Learning Artificial Intelligence Algorithms to Verify N-Nitroso-N-Methylurea and Urethane Positive Control Proliferative Changes in Tg-RasH2 Mouse Carcinogenicity Studies

Autor: Rudmann, Daniel, Albretsen, Jay, Doolan, Colin, Gregson, Mark, Dray, Beth, Sargeant, Aaron, D, Donal O’Shea, Jogile Kuklyte, Power, Adam, Fitzgerald, Jenny
Rok vydání: 2020
Předmět:
ISSN: 0192-6233
DOI: 10.25384/sage.13352995
Popis: Supplemental Material, sj-docx-1-tpx-10.1177_0192623320973986 for Using Deep Learning Artificial Intelligence Algorithms to Verify N-Nitroso-N-Methylurea and Urethane Positive Control Proliferative Changes in Tg-RasH2 Mouse Carcinogenicity Studies by Daniel Rudmann, Jay Albretsen, Colin Doolan, Mark Gregson, Beth Dray, Aaron Sargeant, Donal O’Shea D, Jogile Kuklyte, Adam Power and Jenny Fitzgerald in Toxicologic Pathology
Databáze: OpenAIRE