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Analysing Cerebrospinal Fluid with Explainable Deep Learning: from Diagnostics to Insights.

Leonille SchweizerPhilipp SeegererHee-Yeong KimRené SaitenmacherAmos MuenchLiane BarnickAnja OsterlohCarsten DittmayerRuben JödickeDebora PehlAnnekathrin ReinhardtKlemens RuprechtWerner StenzelAnnika K WefersPatrick N HarterUlrich SchüllerFrank L HeppnerMaximilian AlberKlaus-Robert MüllerFrederick Klauschen
Published in: Neuropathology and applied neurobiology (2022)
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
  • cell therapy
  • artificial intelligence
  • convolutional neural network
  • stem cells
  • high resolution
  • high throughput
  • brain injury