Abstract
Objectives This research study aims to advance the staging of Parkinson's disease (PD) by incorporating
machine learning to assess and include a broader multifunctional spectrum of neurocognitive
symptoms in the staging schemes beyond motor-centric assessments. Specifically, we
provide a novel framework to modernize and personalize PD staging more objectively
by proposing a hybrid feature scoring approach.
Methods We recruited 37 individuals diagnosed with PD, each of whom completed a series of
tablet-based neurocognitive tests assessing motor, memory, speech, executive functions,
and tasks ranging in complexity from single to multifunctional. Then, the collected
data were used to develop a hybrid feature scoring system to calculate a weighted
vector for each function. We evaluated the current PD staging schemes and developed
a new approach based on the features selected and extracted using random forest and
principal component analysis.
Results Our findings indicate a substantial bias in current PD staging systems toward fine
motor skills, that is, other neurological functions (memory, speech, executive function,
etc.) do not map into current PD stages as well as fine motor skills do. The results
demonstrate that a more accurate and personalized assessment of PD severity could
be achieved by including a more exhaustive range of neurocognitive functions in the
staging systems either by involving multiple functions in a unified staging score
or by designing a function-specific staging system.
Conclusion The proposed hybrid feature score approach provides a comprehensive understanding
of PD by highlighting the need for a staging system that covers various neurocognitive
functions. This approach could potentially lead to more effective, objective, and
personalized treatment strategies. Further, this proposed methodology could be adapted
to other neurodegenerative conditions such as Alzheimer's disease or amyotrophic lateral
sclerosis.
Keywords
machine learning - Parkinson's disease - disease staging - digital health - neurocognitive
disorder
