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» Authors » Alvaro E Ulloa Cerna

Alvaro E Ulloa Cerna

Explore the profile of Alvaro E Ulloa Cerna including associated specialties, affiliations and a list of published articles. Areas
Snapshot
Articles 5
Citations 137
Followers 0
Related Specialties
General Medicine
Molecular Biology
Biomedical Engineering
Top 10 Co-Authors
Brandon K Fornwalt
Christopher M Haggerty
Sushravya Raghunath
Linyuan Jing
David P vanMaanen
Joseph B Leader
Dustin N Hartzel
H Lester Kirchner
Joshua V Stough
John M Pfeifer
Published In
JACC Heart Fail
Int J Cardiovasc Imaging
Nat Med
J Electrocardiol
Nat Biomed Eng
Affiliations
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Recent Articles
1.
A Large-scale Multimodal Study for Predicting Mortality Risk Using Minimal and Low Parameter Models and Separable Risk Assessment
Cerna A, vanMaanen D, Jing L, Stough J, Patel A, Haggerty C, et al.
IEEE J Biomed Health Inform . 2025 Mar; PP. PMID: 40031034
The majority of biomedical studies use limited datasets that may not generalize over large heterogeneous datasets that have been collected over several decades. The current paper develops and validates several...
2.
An ECG-based machine learning model for predicting new-onset atrial fibrillation is superior to age and clinical features in identifying patients at high stroke risk
Raghunath S, Pfeifer J, Kelsey C, Nemani A, Ruhl J, Hartzel D, et al.
J Electrocardiol . 2022 Nov; 76:61-65. PMID: 36436476
Background: Several large trials have employed age or clinical features to select patients for atrial fibrillation (AF) screening to reduce strokes. We hypothesized that a machine learning (ML) model trained...
3.
Generalizability and quality control of deep learning-based 2D echocardiography segmentation models in a large clinical dataset
Zhang X, Cerna A, Stough J, Chen Y, Carry B, Alsaid A, et al.
Int J Cardiovasc Imaging . 2022 Feb; 38(8):1685-1697. PMID: 35201510
Use of machine learning (ML) for automated annotation of heart structures from echocardiographic videos is an active research area, but understanding of comparative, generalizable performance among models is lacking. This...
4.
Deep-learning-assisted analysis of echocardiographic videos improves predictions of all-cause mortality
Cerna A, Jing L, Good C, vanMaanen D, Raghunath S, Suever J, et al.
Nat Biomed Eng . 2021 Feb; 5(6):546-554. PMID: 33558735
Machine learning promises to assist physicians with predictions of mortality and of other future clinical events by learning complex patterns from historical data, such as longitudinal electronic health records. Here...
5.
Prediction of mortality from 12-lead electrocardiogram voltage data using a deep neural network
Raghunath S, Cerna A, Jing L, vanMaanen D, Stough J, Hartzel D, et al.
Nat Med . 2020 May; 26(6):886-891. PMID: 32393799
The electrocardiogram (ECG) is a widely used medical test, consisting of voltage versus time traces collected from surface recordings over the heart. Here we hypothesized that a deep neural network...
6.
A Machine Learning Approach to Management of Heart Failure Populations
Jing L, Cerna A, Good C, Sauers N, Schneider G, Hartzel D, et al.
JACC Heart Fail . 2020 May; 8(7):578-587. PMID: 32387064
Background: Heart failure is a prevalent, costly disease for which new value-based payment models demand optimized population management strategies. Objectives: This study sought to generate a strategy for managing populations...