Cargando…
Development of Training Materials for Pathologists to Provide Machine Learning Validation Data of Tumor-Infiltrating Lymphocytes in Breast Cancer
SIMPLE SUMMARY: The High Throughput Truthing project aims to develop a dataset of stromal tumor-infiltrating lymphocytes (sTILs) density evaluations in hematoxylin and eosin-stained invasive breast cancer specimens fit for a regulatory purpose. After completion of the pilot study, the analysis demon...
Autores principales: | Garcia, Victor, Elfer, Katherine, Peeters, Dieter J. E., Ehinger, Anna, Werness, Bruce, Ly, Amy, Li, Xiaoxian, Hanna, Matthew G., Blenman, Kim R. M., Salgado, Roberto, Gallas, Brandon D. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9139395/ https://www.ncbi.nlm.nih.gov/pubmed/35626070 http://dx.doi.org/10.3390/cancers14102467 |
Ejemplares similares
-
Pilot study to evaluate tools to collect pathologist annotations for validating machine learning algorithms
por: Elfer, Katherine, et al.
Publicado: (2022) -
A Pathologist-Annotated Dataset for Validating Artificial Intelligence: A Project Description and Pilot Study
por: Dudgeon, Sarah N., et al.
Publicado: (2021) -
Tumor Infiltrating Lymphocytes (TILS) and PD-L1 Expression in Breast Cancer: A Review of Current Evidence and Prognostic Implications from Pathologist’s Perspective
por: Angelico, Giuseppe, et al.
Publicado: (2023) -
Problems for Pathologists
Publicado: (1876) -
The Pathologist as Poet
por: Domen, Ronald E.
Publicado: (2016)