Alvaro Ulloa

According to our database, Alvaro Ulloa authored at least 13 papers between 2014 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

A Review of Machine Learning Methods Applied to Video Analysis Systems.

Marios S. Pattichis, Venkatesh Jatla, Alvaro E. Ulloa Cerna

Proceedings of the 57th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2023, Pacific Grove, CA, USA, October 29, 2023

2019

Deep neural networks can predict mortality from 12-lead electrocardiogram voltage data.

Sushravya Raghunath, Alvaro E. Ulloa Cerna, Linyuan Jing, David P. vanMaanen, Joshua Stough, Dustin N. Hartzel, Joseph B. Leader, H. Lester Kirchner, Christopher W. Good, Aalpen A. Patel, Brian P. Delisle, Amro Alsaid, Dominik Beer, Christopher M. Haggerty, Brandon K. Fornwalt

CoRR, 2019

Interpretable Neural Networks for Predicting Mortality Risk using Multi-modal Electronic Health Records.

Alvaro E. Ulloa Cerna, Marios Pattichis, David P. vanMaanen, Linyuan Jing, Aalpen A. Patel, Joshua V. Stough, Christopher M. Haggerty, Brandon K. Fornwalt

CoRR, 2019

Automatic Classification of Radiological Report for Intracranial Hemorrhage.

Kamal Jnawali, Mohammad R. Arbabshirani, Alvaro E. Ulloa, Navalgund Rao, Aalpen A. Patel

Proceedings of the 13th IEEE International Conference on Semantic Computing, 2019

2018

A deep neural network predicts survival after heart imaging better than cardiologists.

Alvaro Ulloa, Linyuan Jing, Christopher W. Good, David P. vanMaanen, Sushravya Raghunath, Jonathan D. Suever, Christopher D. Nevius, Gregory J. Wehner, Dustin N. Hartzel, Joseph B. Leader, Amro Alsaid, Aalpen A. Patel, H. Lester Kirchner, Christopher M. Haggerty, Brandon K. Fornwalt

CoRR, 2018

Improving Classification Rate of Schizophrenia Using a Multimodal Multi-Layer Perceptron Model with Structural and Functional MR.

Alvaro Ulloa, Sergey M. Plis, Vince D. Calhoun

CoRR, 2018

2015

Synthetic structural magnetic resonance image generator improves deep learning prediction of schizophrenia.

Alvaro Ulloa, Sergey M. Plis, Erik B. Erhardt, Vince D. Calhoun

Proceedings of the 25th IEEE International Workshop on Machine Learning for Signal Processing, 2015

Generation of synthetic structural magnetic resonance images for deep learning pre-training.

Eduardo Castro, Alvaro Ulloa, Sergey M. Plis, Jessica A. Turner, Vince D. Calhoun

Proceedings of the 12th IEEE International Symposium on Biomedical Imaging, 2015

2014

A three-way parallel ICA approach to analyze links among genetics, brain structure and brain function.

Victor M. Vergara, Alvaro Ulloa, Vince D. Calhoun, David Boutte, Jiayu Chen, Jingyu Liu

NeuroImage, 2014

A quasi-local method for instantaneous frequency estimation with application to structural magnetic resonance images.

Alvaro Ulloa, Paul Rodríguez, Jingyu Liu, Vince D. Calhoun, Marios S. Pattichis

Proceedings of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014

Three-way parallel independent component analysis for imaging genetics using multi-objective optimization.

Alvaro Ulloa, Jingyu Liu, Victor M. Vergara, Jiayu Chen, Vince D. Calhoun, Marios S. Pattichis

Proceedings of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014

Parallel ICA with multiple references: A semi-blind multivariate approach.

Jiayu Chen, Vince D. Calhoun, Alvaro E. Ulloa, Jingyu Liu

Proceedings of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014

Detecting volumetric changes in fMRI connectivity networks in schizophrenia patients.

Mohammad R. Arbabshirani, Marios S. Pattichis, Alvaro Ulloa, Vince D. Calhoun

Proceedings of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014