Development of Training Materials for Pathologists to Provide Machine Learning Validation Data of Tumor-Infiltrating Lymphocytes in Breast Cancer

Development of Training Materials for Pathologists to Provide Machine Learning Validation Data of Tumor-Infiltrating Lymphocytes in Breast Cancer

The High Throughput Truthing project aims to develop a dataset for validating artificial intelligence and machine learning models (AI/ML) fit for regulatory purposes. The context of this AI/ML validation dataset is the reporting of stromal tumor-infiltrating lymphocytes (sTILs) density evaluations i...

Full description

Bibliographic Details
Main Authors: Victor Garcia, Katherine Elfer, Dieter J. E. Peeters, Anna Ehinger, Bruce Werness, Amy Ly, Xiaoxian Li, Matthew G. Hanna, Kim R. M. Blenman, Roberto Salgado, Brandon D. Gallas
Format: Article
Language:English
Published: MDPI AG 2022-05-01
Series:Cancers
Subjects:
tumor-infiltrating lymphocytes
pathologist training/education
expert panel
validation dataset
biomarker
Online Access:https://www.mdpi.com/2072-6694/14/10/2467

Internet

https://www.mdpi.com/2072-6694/14/10/2467

Similar Items