HFW-NPO: A Dual a Paradigm Hybrid Filter–Wrapper Nomadic People Optimizer Framework for High-Dimensional Alzheimer’s Gene Expression Classification

Almuntadher Mahmood Alwhelat

doi:10.3390/electronics15132970

HFW-NPO: A Dual a Paradigm Hybrid Filter–Wrapper Nomadic People Optimizer Framework for High-Dimensional Alzheimer’s Gene Expression Classification

2026-07-08

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Almuntadher Mahmood Alwhelat *

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Rahib H. Abiyev

DOI：10.3390/electronics15132970

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Alzheimer’s Disease (AD) necessitates high-resolution transcriptomic biomarkers for early detection, yet current computational methods are hampered by high-dimensional search space and publication bias regarding imbalanced datasets. We propose the Hybrid Filter–Wrapper Nomadic People Optimizer, a three-stage pipeline integrating a tri-criterion filter, an enhanced NPO wrapper with adaptive Lévy-scale anti-stagnation mechanism, and a five-member soft-voting ensemble. The system was evaluated using a dual-paradigm protocol; Scenario A (balance brain tissue; GEO dataset GSE 33000, GSE 132903, GSE122063) and Scenario B (imbalanced peripheral blood: GSE 63060 + GSE 636061). In scenario A, HFW-NPO outperformed 13 published methods, achieving balanced accuracy of 85.28%, 87.16%, and 96.67% while identifying compact panels of 29–32 probes per fold (observed range: 24–38). Scenario B, evaluated on a merged 478-samples peripheral blood cohort (GSE63060 + GSE 636061 imbalanced 1.48:1) with z-score batch harmonization and RSKF (5 × 10) cross-validation, achieved a balanced accuracy of 59.53% and MCI Recall of 63.50 ± 14.02%, providing the first reproducible baseline for this clinically challenging task, while acknowledging that 59.53% balanced accuracy does not yet reach clinically actionable levels. By providing transparent reporting across both balanced and severely imbalanced datasets, this study establishes a state-of-the-art, reproducible framework for AD biomarker discovery and provides a critical baseline for the challenging task of transcriptomic-based classification in peripheral blood samples. Result is currently scoped to Illumina HumanHT-12 microarray data, and cross-platform validation on RNA-seq cohorts is identified as a priority future extension.

Keywords:

Alzheimer’s disease

gene expression classification

feature selection

Nomadic People Optimizer

imbalanced learning

bioinformatics

HFW-NPO: A Dual a Paradigm Hybrid Filter–Wrapper Nomadic People Optimizer Framework for High-Dimensional Alzheimer’s Gene Expression Classification

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