Escudero, Javier

Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations

Moguilner, S., Baez, S., Hernandez, H., Migeot, J., Legaz, A., Gonzalez-Gomez, R., Farina, F. R., Prado, P., Cuadros, J., Tagliazucchi, E., et al. (2024) · Nature Medicine

Dementia and Cognitive Impairment ResearchFunctional Brain Connectivity Studies

Cited by 128

Machine Learning-Based Method for Personalized and Cost-Effective Detection of Alzheimer's Disease

Escudero, J., Ifeachor, E., Zajicek, J. P., Green, C., Shearer, J., & Pearson, S. (2013) · IEEE Transactions on Biomedical Engineering

Dementia and Cognitive Impairment ResearchArtificial Intelligence in Healthcare

Cited by 107

Deep learning of resting-state electroencephalogram signals for three-class classification of Alzheimer’s disease, mild cognitive impairment and healthy ageing

Huggins, C. J., Escudero, J., Parra, M. A., Scally, B., Anghinah, R., Vitória Lacerda De Araújo, A., Basile, L. F., & Abasolo, D. (2021) · Journal of Neural Engineering

EEG and Brain-Computer InterfacesDementia and Cognitive Impairment Research

Cited by 105

An Efficient Mixture of Deep and Machine Learning Models for COVID-19 and Tuberculosis Detection Using X-Ray Images in Resource Limited Settings

Al-Timemy, A. H., Khushaba, R. N., Mosa, Z. M., & Escudero, J. (2021) · Studies in Systems, Decision and Control

COVID-19 diagnosis using AIRadiomics and Machine Learning in Medical Imaging

Cited by 41

Structural inequality and temporal brain dynamics across diverse samples

Baez, S., Hernandez, H., Moguilner, S., Cuadros, J., Santamaria‐Garcia, H., Medel, V., Migeot, J., Cruzat, J., Valdes‐Sosa, P. A., Lopera, F., et al. (2024) · Clinical and Translational Medicine

Neural dynamics and brain functionFunctional Brain Connectivity Studies

Cited by 21