What is MOPS?
-
MOPS (Mathematical optimization of Parkinson's scale) is a data-driven method to optimize the clinical scales for Parkinson’s disease, improving its ability to track disease progression.
-
It uses optimization formulations to learn which items and scoring thresholds most strongly reflect true disease trajectory, while down-weighting noisy or redundant items.
-
MOPS also offers a score based only on self-reported items.
-
Learned weights based on PPMI data: using all items, using self-reported items only.
Where can I find the paper and software?
-
The MOPS code is available on GitHub.
-
The MOPS paper is available as a preprint at medRxiv.
Where can I see an example of the outcome?
-
Based on our results, we've created an online self-reported questionnaire that achieves good consistency with only 11 simple questions. It is available here.
How to cite MOPS?
A. Benesh, R. N. Alcalay, A. Mirelman, R. Shamir.
``Optimizing Parkinson’s Disease progression scales using computational methods''.
medRxiv https://doi.org/10.1101/2025.07.31.25332494 (2025).
How can I get in touch?
