[Opportunities and challenges in the pathological diagnosis of pediatric tumors in the molecular and artificial intelligence era].

Abstract

Pediatric tumors differ significantly from adult cancers, possessing unique developmental origins, histological features, and molecular genetic changes. With the rapid advancement of multi-omics technologies, such as genomics, transcriptomics, proteomics, and epigenetic analyses, the molecular characteristics of pediatric tumors have been extensively revealed, providing new possibilities for precision medicine. Concurrently, the integration of artificial intelligence and digital pathology has effectively enhanced diagnostic accuracy, presenting a broad scope for future development. While this progress positively impacts the pathological diagnosis of pediatric tumors, it also presents challenges related to data complexity, technology integration, and the promotion of clinical applications. This article aims to discuss the influence of molecular and artificial intelligence, as well as multimodal integrated pathological models on diagnosis and prognostic prediction of pediatric tumor, with the goal of fostering further exploration and in-depth research.

Ähnliche Arbeiten