Information theory approaches to improve glioma diagnostic workflows in surgical neuropathology.

ABSTRACT:

Aims

Resource-strained healthcare ecosystems often struggle with the adoption of the World Health Organization (WHO) recommendations for the classification of central nervous system (CNS) tumors. The generation of robust clinical diagnostic aids and the advancement of simple solutions to inform investment strategies in surgical neuropathology would improve patient care in these settings.

Methods

We used simple information theory calculations on a brain cancer simulation model and real-world data sets to compare contributions of clinical, histologic, immunohistochemical, and molecular information. An image noise assay was generated to compare the efficiencies of different image segmentation methods in H&E and Olig2 stained images obtained from digital slides. An auto-adjustab

SUBMITTER: Cevik L 

PROVIDER: S-EPMC9425010 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature