Pathologist-Read vs AI-Driven Assessment of Tumor-Infiltrating Lymphocytes in Melanoma.

ABSTRACT:

Importance

Tumor-infiltrating lymphocytes (TILs) are a provocative biomarker in melanoma, influencing diagnosis, prognosis, and immunotherapy outcomes; however, traditional pathologist-read TIL assessment on hematoxylin and eosin-stained slides is prone to interobserver variability, leading to inconsistent clinical decisions. Therefore, development of newer TIL scoring approaches that produce more reliable and consistent readouts is important.

Objective

To evaluate the analytical and clinical validity of a machine learning algorithm for TIL quantification in melanoma compared with traditional pathologist-read methods.

Design, setting, and participants

This multioperator, global, multi-institutional prognostic study compared TIL scoring reproducibility between traditio

SUBMITTER: Aung TN 

PROVIDER: S-EPMC12232186 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature