Author

Camilo E. Valderrama

The University of WinnipegORCID 0000-0001-5333-8265Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:differential expression· 1 Assay:electronic health records· 1 Assay:imaging· 1

Frequent Co-Authors

Luis Villaseñor-PinedaiD· 1 shared Qian LiuiD· 1 shared Rogelio Sotero Reyes-GalaviziD· 1 shared Shyamal Y. DhariaiD· 1 shared Stephen D. SmithiD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

5 top collaborators · 4 mutual co-author links

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1 shared paperNeuroscience

Luis Villaseñor-PinedaORCID

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2 papers

Recent·Most cited

NeuroscienceJournal of Neural EngineeringPeer-reviewedFeb 23, 2026

Exploring the Interaction of APOE-ϵ4 and PICALM rs3851179 With Dynamic Functional Connectivity in Healthy Middle-Aged Adults at Risk for Alzheimer's Disease

Shyamal Y. Dharia, Camilo E. Valderrama, Qian Liu, Stephen D. Smith

This study uses resting-state fMRI to analyze dynamic functional connectivity dwell-time patterns in middle-aged adults to differentiate Alzheimer's disease genetic risk profiles.

DOI 10.1088/1741-2552/ae4926

humanimaging

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NeurosciencebioRxivPreprintMar 5, 2025

Automatic detection of nociceptive pain levels using frequency bands from electroencephalographic (EEG) signals

Rogelio Sotero Reyes-Galaviz, Luis Villaseñor-Pineda, Camilo E. Valderrama

This paper uses EEG signals to detect nociceptive pain levels, achieving 83% accuracy in distinguishing high and low pain based on frequency band power.

DOI 10.1101/2025.03.05.641582

humanelectronic health records

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