The analytical and clinical validity of AI algorithms to score TILs in TNBC: can we use different machine learning models interchangeably?

ABSTRACT:

Background

Pathologist-read tumor-infiltrating lymphocytes (TILs) have showcased their predictive and prognostic potential for early and metastatic triple-negative breast cancer (TNBC) but it is still subject to variability. Artificial intelligence (AI) is a promising approach toward eliminating variability and objectively automating TILs assessment. However, demonstrating robust analytical and prognostic validity is the key challenge currently preventing their integration into clinical workflows.

Methods

We evaluated the impact of ten AI models on TILs scoring, emphasizing their distinctions in TILs analytical and prognostic validity. Several AI-based TILs scoring models (seven developed and three previously validated AI models) were tested in a retrospective analytical coh

SUBMITTER: Vidal JM 

PROVIDER: S-EPMC11615110 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature