Grading of lung adenocarcinomas with simultaneous segmentation by artificial intelligence (GLASS-AI).

ABSTRACT: Preclinical genetically engineered mouse models (GEMMs) of lung adenocarcinoma are invaluable for investigating molecular drivers of tumor formation, progression, and therapeutic resistance. However, histological analysis of these GEMMs requires significant time and training to ensure accuracy and consistency. To achieve a more objective and standardized analysis, we used machine learning to create GLASS-AI, a histological image analysis tool that the broader cancer research community can utilize to grade, segment, and analyze tumors in preclinical models of lung adenocarcinoma. GLASS-AI demonstrates strong agreement with expert human raters while uncovering a significant degree of unreported intratumor heterogeneity. Integrating immunohistochemical staining with high-resolution grade anal

SUBMITTER: Lockhart JH 

PROVIDER: S-EPMC10354042 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature