LINNDA: Lymphoma identification through neural network detection aid.

ABSTRACT: Preoperative differentiation between primary central nervous system lymphoma (PCNSL) and glioblastoma (GBM) is crucial for appropriate management and surgical planning. This study aims to evaluate the diagnostic performance of the AI-assisted workflow, LINNDA (lymphoma identification through neural network detection aid), in comparison to that of human raters. In total, ten clinicians independently reviewed 46 cases of GBM and PCNSL. The LINNDA workflow evaluated all 1,470 possible pairwise combinations. For each pair, whenever two clinicians disagreed, a DenseNet169 neural network was explicitly integrated as a third independent diagnostic opinion ("tie-breaker"). Integrating the AI-generated predictions improved overall accuracy to 89.9%, exceeding the expert consensus. We further establ

SUBMITTER: Naser PV 

PROVIDER: S-EPMC12752750 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature