Identifying invasiveness to aid lung adenocarcinoma diagnosis using deep learning and pathomics
Sign Up to like & getrecommendations! Published in 2025 at "Scientific Reports"
DOI: 10.1038/s41598-025-87094-5
Abstract: Most classification efforts for primary subtypes of lung adenocarcinoma (LUAD) have not yet been integrated into clinical practice. This study explores the feasibility of combining deep learning and pathomics to identify tumor invasiveness in LUAD… read more here.
Keywords: deep learning; learning pathomics; lung adenocarcinoma; tumor ... See more keywords
Construction and validation of a prognostic nomogram model integrating machine learning-pathomics and clinical features in IDH-wildtype glioblastoma
Sign Up to like & getrecommendations! Published in 2025 at "Journal of Translational Medicine"
DOI: 10.1186/s12967-025-06482-7
Abstract: Novel diagnostic criteria for glioblastoma (GBM) in the 2021 WHO classification emphasize the importance of integrating pathological and molecular features. Pathomics, which involves the extraction of digital pathology data, is gaining significant interest in the… read more here.
Keywords: learning pathomics; model integrating; machine learning; model ... See more keywords