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HarmonyTM: multi-center data harmonization applied to distributed learning for Parkinson's disease classification.

Raissa SouzaEmma A M StanleyVedant GulveJasmine A MooreChris KangRichard CamicioliOury MonchiZahinoor IsmailMatthias WilmsNils Daniel Forkert
Published in: Journal of medical imaging (Bellingham, Wash.) (2024)
HarmonyTM is a method tailored for harmonizing 3D neuroimaging data within the TM approach, aiming to minimize shortcut learning in distributed setups. This prevents the disease classifier from leveraging scanner-specific details to classify patients with or without PD-a key aspect for deploying ML models for clinical applications.
Keyphrases
  • electronic health record
  • big data
  • machine learning
  • mouse model
  • magnetic resonance
  • magnetic resonance imaging
  • data analysis
  • artificial intelligence