Analysing cerebrospinal fluid with explainable deep learning: From diagnostics to insights.

Leonille Schweizer Philipp SeegererHee-Yeong KimRené SaitenmacherAmos MuenchLiane BarnickAnja OsterlohCarsten DittmayerRuben JödickeDebora PehlAnnekathrin ReinhardtKlemens RuprechtWerner Stenzel Annika K WefersPatrick N HarterUlrich SchüllerFrank L HeppnerMaximilian AlberKlaus-Robert MüllerFrederick Klauschen

Published in: Neuropathology and applied neurobiology (2023)

Our approach provides the basis to overcome current limitations in automated cell classification for routine diagnostics and demonstrates how a visual explanation framework can connect machine decision-making with cell properties and thus provide a novel versatile and quantitative method for investigating CSF manifestations of various neurological diseases.

Keyphrases

deep learning
cerebrospinal fluid
machine learning
single cell
decision making
artificial intelligence
cell therapy
convolutional neural network
stem cells
high resolution
high throughput
clinical practice
bone marrow