FDG-PET combined with learning vector quantization allows classification of neurodegenerative diseases and reveals the trajectory of idiopathic REM sleep behavior disorder

• Published in: Computer methods and programs in biomedicine Vol. 225; p. 107042
• Main Authors: van Veen, Rick, Meles, Sanne K., Renken, Remco J., Reesink, Fransje E., Oertel, Wolfgang H., Janzen, Annette, de Vries, Gert-Jan, Leenders, Klaus L., Biehl, Michael
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.10.2022
• Subjects: FDG-PET; Idiopathic REM sleep behavior disorder trajectories; Learning vector quantization; Neurodegenerative diseases; Relevance learning; SSM/PCA; FDG-PET; Idiopathic REM sleep behavior disorder trajectories; Relevance learning; Neurodegenerative diseases; Learning vector quantization; SSM/PCA

•Differential diagnosis of Parkinson’s disease, Alzheimer’s disease, and dementia with Lewy bodies based on FDG-PET data.•Longitudinal REM sleep behavior disorder conversion trajectory analysis.•Explainable and actionable learning vector quantization and relevance learning in neuroradiology.•Visuali...