Clinical Neurology and Neurosurgery • Vol 258
Unsupervised machine learning identifies clinically relevant patterns of CSF dynamic dysfunction in normal pressure hydrocephalus
September 2025 • Emanuele Camerucci, Petrice M. Cogswell, Jeffrey L. Gunter, Matthew L. Senjem, Matthew C. Murphy, Jonathan Graff-Radford, Ignacio Jusué-Torres, David…
NMF-generated patterns of CSF distribution showed high accuracy in discerning individuals with iNPH from controls. The patterns most relying on DESH features showed highest potential for independently predicting NPH diagnosis. The algorithm we proposed should not be perceived as a replacement for human expertise but rather as an additional tool to assist clinicians in achieving accurate diagnoses.