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Journal Articles by A. E. Ulloa

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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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Conference Papers

K. Jnawali, M. Arbabshirani, A. Ulloa, and A. Patel
Hybrid CNN and LSTM Deep Learning Architecture for Radiological Report Classification
IEEE BHI, 2018
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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
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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
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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
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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
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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
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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
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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
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Abstracts

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
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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
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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
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Theses

A. E. Ulloa
Large Scale Electronic Health Record Data and Echocardiography Video Analysis for Mortality Risk Prediction
University of New Mexico, 2019
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A. Ulloa
Data Driven Sample Generator Model with Application to Classification
Statistics, MS thesis, 2016
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A. Ulloa
AM-FM Analysis of Structural and Functional Magnetic Resonance Images
Electrical and Computer Engineering, MS Thesis, 2013
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A. Ulloa
Diseno y comparacion de metodos para la deteccion automatica de defectos en telas
Electrical and Computer Engineering, BS Thesis, 2010
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