Radio-pathomic approaches in pediatric neuro-oncology: Opportunities and challenges.

ABSTRACT: With medical software platforms moving to cloud environments with scalable storage and computing, the translation of predictive artificial intelligence (AI) models to aid in clinical decision-making and facilitate personalized medicine for cancer patients is becoming a reality. Medical imaging, namely radiologic and histologic images, has immense analytical potential in neuro-oncology, and models utilizing integrated radiomic and pathomic data may yield a synergistic effect and provide a new modality for precision medicine. At the same time, the ability to harness multi-modal data is met with challenges in aggregating data across medical departments and institutions, as well as significant complexity in modeling the phenotypic and genotypic heterogeneity of pediatric brain tumors. In this

SUBMITTER: Familiar AM 

PROVIDER: S-EPMC10576517 | biostudies-literature | 2023 Jan-Dec

REPOSITORIES: biostudies-literature