CRISP: a correlation-filtered recursive feature elimination and integration of SMOTE pipeline for gait-based Parkinson’s disease screening
CRISP is the first VGRF-based pipeline to combine correlation-filtered feature pruning, recursive feature elimination, and SMOTE to enhance PD detection performance, while also introducing a subject-wise evaluation protocol that captures patient-level variability for truly personalized diagnostics. These twin novelties deliver clinically significant gains and lay the foundation for real-time, on-device PD detection and severity monitoring.
Authors
- Asim Waris (ORCID: https://orcid.org/0000-0002-0190-0700)
- Fawwaz Hazzazi (ORCID: https://orcid.org/0000-0002-9925-673X)
- Namra Afzal
- Muhammad Adeel Ijaz (ORCID: https://orcid.org/0009-0008-8138-0477)
- Hasnain Ali (ORCID: https://orcid.org/0000-0002-4530-5356)
- Muhammad Jawad Khan (ORCID: https://orcid.org/0000-0001-9638-2565)
- Syed Omer Gilani (ORCID: https://orcid.org/0000-0001-5654-7863)
- Javaid Iqbal (ORCID: https://orcid.org/0000-0001-9601-2302)
Institutions
- Abu Dhabi University (AE)
- Prince Sattam Bin Abdulaziz University (SA)
- National University of Sciences and Technology (PK)
Publication Details
- Journal
- Frontiers in Computational Neuroscience
- Published
- 2025-10-10
- DOI
- https://doi.org/10.3389/fncom.2025.1660963
- Primary Topic
- Parkinson's Disease Mechanisms and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00