Publications

@article{JA25125,

title = {Symmetry in Genetic Distance Metrics: Quantifying Variability in Neurological Disorders for Personalized Treatment of Alzheimer’s and Dementia},

author = {Jorge A. Ruiz-Vanoye and Ocotlán Díaz-Parra and Marco A. Márquez-Vera and Ricardo A. Barrera-Cámara and Alejandro Fuentes-Penna and Eric Simancas-Acevedo and Miguel A. Ruiz-Jaimes and Juan Xicoténcatl-Pérez and Julio C . Ramos-Fernández},

doi = {https://doi.org/10.3390/sym17020172},

issn = {2073-8994},

year  = {2025},

date = {2025-01-20},

journal = {Symmetry},

abstract = {This paper aims to adapt and apply genetic distance metrics in biomedical signal processing to improve the classification and monitoring of neurological disorders, specifically Alzheimer’s disease and frontotemporal dementia. The primary objectives are: (1) to quantify the variability in EEG signal patterns among the distinct subtypes of neurodegenerative disorders and healthy individuals, and (2) to explore the potential of a novel genetic similarity metric in establishing correlations between brain signal dynamics and clinical progression. Using a dataset of resting-state EEG recordings (eyes closed) from 88 subjects (36 with Alzheimer’s disease, 23 with frontotemporal dementia, and 29 healthy individuals), a comparative analysis of brain activity patterns was conducted. Symmetry plays a critical role in the proposed genetic similarity metric, as it captures the balanced relationships between intra- and inter-group EEG signal patterns. Our findings demonstrate that this approach significantly improves disease subtype identification and highlights the potential of the genetic similarity metric to optimize the predictive models. Furthermore, this methodology supports the development of personalized therapeutic interventions tailored to individual patient profiles, making a novel contribution to the field of neurological signal analysis and advancing the application of EEG in personalized medicine.},

keywords = {Bio-Medicina, Papers in the Science Citation Index Expanded},

pubstate = {published},

tppubtype = {article}

}