Application of novel hybrid machine learning systems and radiomics features for non-motor outcome prediction in Parkinson's disease.

Mohammadreza SalmapourMahya BakhtiaryMahdi HosseinZadehMehdi MaghsudiFereshteh YousefiriziMohammad Mahdi GhaemiXinchi Hou

Published in: Physics in medicine and biology (2022)

Our study shows the importance of using larger datasets (timeless), and utilizing optimized HMLSs, for significantly improved prediction of MoCA in PD patients.

Keyphrases

machine learning
end stage renal disease
newly diagnosed
ejection fraction
chronic kidney disease
prognostic factors
magnetic resonance imaging
computed tomography
lymph node metastasis
deep learning
rna seq