Plain text, RIS, BibTex

2022
X. Zhang, A. E. U. Cerna, J. V. Stough, Y. Chen, B. J. Carry, A. Alsaid, S. Raghunath, D. P. vanMaanen, et al.
Generalizability and quality control of deep learning-based 2D echocardiography segmentation models in a large clinical dataset
The International Journal of Cardiovascular Imaging, 2022
URL, DOI, PDF, RIS, BibTex

2021
E.-M. Yasser, M. Abbas, I. Hoaglund, A. U. Cerna, T. B. Morland, C. M. Haggerty, E. S. Hall, and B. K. Fornwalt
OASIS+: leveraging machine learning to improve the prognostic accuracy of OASIS severity score for predicting in-hospital mortality
BMC medical informatics and decision making, 21(1), 2021
PDF, RIS, BibTex
S. Raghunath, J. M. Pfeifer, A. Ulloa, A. Nemani, T. Carbonati, L. Jing, D. P. vanMaanen, D. N. Hartzel, et al.
Deep Neural Networks Can Predict New-Onset Atrial Fibrillation From the 12-Lead Electrocardiogram and Help Identify Those at Risk of AF-Related Stroke
Circulation, 2021
PDF, RIS, BibTex
A. Ulloa, L. Jing, C. W. Good, S. Raghunath, J. D. Suever, C. D. Nevius, G. J. Wehner, D. N. Hartzel, et al.
Deep-learning-assisted analysis of echocardiographic videos improves predictions of all-cause mortality
Nature Biomedical Engineering, 2021
PDF, Supplementary Material, RIS, BibTex
A. E. Ulloa-Cerna, L. Jing, J. M. Pfeifer, S. Raghunath, J. A. Ruhl, D. B. Rocha, J. B. Leader, N. Zimmerman, et al.
rECHOmmend: an ECG-based machine-learning approach for identifying patients at high-risk of undiagnosed structural heart disease detectable by echocardiography
medRxiv, 2021
URL, DOI, RIS, BibTex

2020
S. Raghunath, A. Ulloa, L. Jing, J. Stough, D. N. Hartzel, J. B. Leader, H. L. Kirchner, M. C. Stumpe, et al.
Prediction of mortality from 12-lead electrocardiogram voltage data using a deep neural network
Nature medicine, 26(6), 2020
PDF, RIS, BibTex
L. Jing, A. Ulloa, C. W. Good, N. M. Sauers, G. Schneider, D. N. Hartzel, J. B. Leader, H. L. Kirchner, et al.
A machine learning approach to management of heart failure populations
Heart Failure, 8(7), 2020
PDF, RIS, BibTex

2019
J. D. Lewine, S. Plis, A. Ulloa, C. Williams, M. Spitz, J. Foley, K. Paulson, J. Davis, et al.
Quantitative EEG Biomarkers for Mild Traumatic Brain Injury
Journal of Clinical Neurophysiology, 36(4), 2019
PDF, RIS, BibTex
A. E. Ulloa
Large Scale Electronic Health Record Data and Echocardiography Video Analysis for Mortality Risk Prediction
University of New Mexico, 2019
URL, RIS, BibTex

2018
M. D. Samad, A. Ulloa, G. J. Wehner, L. Jing, D. Hartzel, C. W. Good, B. A. Williams, C. M. Haggerty, et al.
Predicting survival from large echocardiography and electronic health record datasets: optimization with machine learning
JACC: Cardiovascular Imaging, 2018
PDF, RIS, BibTex
K. Jnawali, M. Arbabshirani, A. Ulloa, and A. Patel
Hybrid CNN and LSTM Deep Learning Architecture for Radiological Report Classification
IEEE BHI, 2018
PDF, RIS, BibTex
A. Ulloa, S. Plis, and V. Calhoun
Improving Classification Rate of Schizophrenia Using a Multimodal Multi-Layer Perceptron Model with Structural and Functional MR
arXiv preprint arXiv:1804.04591, 2018
RIS, BibTex

2017
A. Ulloa, G. Wehner, D. Hartzel, C. Haggerty, and B. Fornwalt
Data-Driven Phenotyping of Patients with Heart Failure using a Deep-learning Cluster Representation of Echocardiographic and Electronic Health Record Data
AHA scientific sessions, 2017
RIS, BibTex
M. Samad, A. Ulloa, G. Wehner, D. Hartzel, C. Haggerty, and B. Fornwalt
Machine Learning-Based Classification of Echocardiographic Measurements Significantly Improves Accuracy in Predicting Mortality over Standard Clinical Variables
AHA scientific sessions, 2017
RIS, BibTex
A. Basile, A. Ulloa, A. Lucas, A. Frase, V. Abedi, M. Ritchie, H. L. Kirchner, C. Manney, et al.
Using a simulation approach to evaluate data-driven algorithms for studying clinical heterogeneity in complex traits
TBC, 2017
PDF, RIS, BibTex

2016
A. Ulloa
Data Driven Sample Generator Model with Application to Classification
Statistics, MS thesis, 2016
PDF, RIS, BibTex
A. Aliper, S. Plis, A. Artemov, A. Ulloa, P. Mamoshina, and A. Zhavoronkov
Deep learning applications for predicting pharmacological properties of drugs and drug repurposing using transcriptomic data
Molecular pharmaceutics, 2016
PDF, RIS, BibTex

2015
A. Ulloa, S. Plis, E. Erhardt, and V. Calhoun
Synthetic structural magnetic resonance image generator improves deep learning prediction of schizophrenia
2015 IEEE 25th International Workshop on Machine Learning for Signal Processing (MLSP), 2015
PDF, RIS, BibTex
E. Castro, A. Ulloa, S. M. Plis, J. A. Turner, and V. D. Calhoun
Generation of synthetic structural magnetic resonance images for deep learning pre-training
2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), 2015
PDF, RIS, BibTex

2014
J. Chen, V. D. Calhoun, A. E. Ulloa, and J. Liu
Parallel ICA with multiple references: A semi-blind multivariate approach
2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014
PDF, RIS, BibTex
M. R. Arbabshirani, M. S. Pattichis, A. Ulloa, and V. D. Calhoun
Detecting volumetric changes in fMRI connectivity networks in schizophrenia patients
2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014
PDF, RIS, BibTex
V. M. Vergara, A. Ulloa, V. D. Calhoun, D. Boutte, J. Chen, and J. Liu
A three-way parallel ICA approach to analyze links among genetics, brain structure and brain function
Neuroimage, 98, 2014
PDF, RIS, BibTex
A. Ulloa, J. Chen, V. M. Vergara, V. Calhoun, and J. Liu
Association between copy number variation losses and alcohol dependence across African American and European American ethnic groups
Alcoholism: Clinical and Experimental Research, 38(5), 2014
PDF, RIS, BibTex
A. Ulloa, P. Rodriguez, J. Liu, V. Calhoun, and M. Pattichis
A quasilocal method for instantaneous frequency estimation with application to structural magnetic resonance images
Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE, 2014
PDF, RIS, BibTex
A. Ulloa, J. Liu, V. Vergara, J. Chen, V. Calhoun, and M. Pattichis
Three-way parallel independent component analysis for imaging genetics using multi-objective optimization
Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE, 2014
independent component analysis matrix decomposition
PDF, RIS, BibTex

2013
A. Ulloa
AM-FM Analysis of Structural and Functional Magnetic Resonance Images
Electrical and Computer Engineering, MS Thesis, 2013
PDF, RIS, BibTex

2012
J. Liu, A. Ulloa, N. Perrone-Bizzozero, R. Yeo, J. Chen, and V. D. Calhoun
A pilot study on collective effects of 22q13. 31 deletions on gray matter concentration in schizophrenia
PloS one, 7(12), 2012
PDF, RIS, BibTex

2010
A. Ulloa
Diseno y comparacion de metodos para la deteccion automatica de defectos en telas
Electrical and Computer Engineering, BS Thesis, 2010
PDF, RIS, BibTex

2009
A. Ulloa and P. Rodriguez
Deteccion automatica de defectos en telas basado en la demodulacion AM-FM
Ibero-American Conference on Trends in Engineering Education and Collaboration, 2009
PDF, RIS, BibTex