A. L. Ribeiro

发表

Automatic Diagnosis of the Short-Duration 12-Lead ECG using a Deep Neural Network: the CODE Study pdf

Thomas B. Schön, Wagner Meira, Derick M. de Oliveira, 2019, ArXiv.

Atrial fibrillation risk prediction from the 12-lead electrocardiogram using digital biomarkers and deep representation learning

J. Behar, A. L. Ribeiro, Shany Biton, 2021, European heart journal. Digital health.

Evaluation of Mortality in Atrial Fibrillation: Clinical Outcomes in Digital Electrocardiography (CODE) Study

Manoel Horta Ribeiro, Gabriela M. M. Paixão, Jéssica A. Canazart, 2020, Global heart.

Association between Atrioventricular Block and Mortality in Primary Care Patients: The CODE Study.

Paulo R. Gomes, D. M. Oliveira, D. Oliveira, 2022, Arquivos brasileiros de cardiologia.

Evaluation of mortality in bundle branch block patients from an electronic cohort: Clinical Outcomes in Digital Electrocardiography (CODE) study.

Manoel Horta Ribeiro, Antônio H. Ribeiro, Gabriela M. M. Paixão, 2019, Journal of electrocardiology.

Genetic analyses of the electrocardiographic QT interval and its components identify additional loci and pathways

M. P. Concas, May E. Montasser, Henry J. Lin, 2022, Nature Communications.

Knowledge Discovery with Electrocardiography Using Interpretable Deep Neural Networks

D. Clifton, A. L. Ribeiro, A. H. Ribeiro, 2022, medRxiv.

Explaining Black-Box Automated Electrocardiogram Classification to Cardiologists

Antônio H. Ribeiro, Gabriela M. M. Paixão, João A. O. Pedrosa, 2020, 2020 Computing in Cardiology.

Clinical and electrocardiographic outcomes evaluated by telemedicine of outpatients with clinical suspicion of COVID-19 treated with chloroquine compounds in Brazil†

Gabriela M. M. Paixão, A. L. Ribeiro, B. Nascimento, 2023, Frontiers in Cardiovascular Medicine.

Automatic diagnosis of the 12-lead ECG using a deep neural network

Manoel Horta Ribeiro, Antônio H. Ribeiro, Gabriela M. M. Paixão, 2019, Nature Communications.

Automated multilabel diagnosis on electrocardiographic images and signals

A. L. Ribeiro, A. Haimovich, W. Schulz, 2021, Nature Communications.

Towards automatic diagnosis of rheumatic heart disease on echocardiographic exams through video-based deep learning

Erickson R. Nascimento, Craig A Sable, Erickson R Nascimento, 2021, J. Am. Medical Informatics Assoc..

Ventricular pre‐excitation in primary care patients: Evaluation of the risk of mortality

Gabriela M. M. Paixão, D. Oliveira, A. L. Ribeiro, 2021, Journal of cardiovascular electrophysiology.

Deep neural network-estimated electrocardiographic age as a mortality predictor

Manoel Horta Ribeiro, Gabriela M. M. Paixão, Thomas Bo Schön, 2021, Nature Communications.

CODE-15%: a large scale annotated dataset of 12-lead ECGs

Thomas B. Schön, Manoel Horta Ribeiro, Antônio H. Ribeiro, 2021 .

Screening for Chagas disease from the electrocardiogram using a deep neural network

Thomas Bo Schön, C. Jidling, A. L. Ribeiro, 2023, medRxiv.

On Merging Feature Engineering and Deep Learning for Diagnosis, Risk Prediction and Age Estimation Based on the 12-Lead ECG

J. Read, J. Behar, A. L. Ribeiro, 2022, IEEE Transactions on Biomedical Engineering.

Pre-trained deep neural network models for age estimation from raw ECG

Thomas B. Schön, Bruce Bartholow Duncan, Manoel Horta Ribeiro, 2021 .

Tele-electrocardiography and bigdata: The CODE (Clinical Outcomes in Digital Electrocardiography) study.

Manoel Horta Ribeiro, Jermana L. Moraes, Antônio H. Ribeiro, 2019, Journal of electrocardiology.

Electrocardiographic Predictors of Mortality: Data from a Primary Care Tele-Electrocardiography Cohort of Brazilian Patients

Manoel Horta Ribeiro, Gabriela M. M. Paixão, P. Macfarlane, 2021, Hearts.

Genetic architecture of spatial electrical biomarkers for cardiac arrhythmia and relationship with cardiovascular disease

M. P. Concas, Henry J. Lin, William J. Young, 2023, Nature Communications.

Association of lifestyle with deep learning predicted electrocardiographic age

L. Brant, Honghuang Lin, A. L. Ribeiro, 2023, Frontiers in Cardiovascular Medicine.

Detection of Arterial Hypertension Through Electrocardiograms

D. Oliveira, A. L. Ribeiro, Wagner Meira, 2022, 2022 Computing in Cardiology (CinC).

Contextualized interpretable machine learning for medical diagnosis

Wagner Meira, Derick M. Oliveira, Antonio L. P. Ribeiro, 2020, Commun. ACM.

Automated classification of cardiology diagnoses based on textual medical reports

Derick M. de Oliveira, Wagner Meira, João A. O. Pedrosa, 2020, J. Inf. Data Manag..

Explaining End-to-End ECG Automated Diagnosis Using Contextual Features

Antônio H. Ribeiro, Gabriela M. M. Paixão, João A. O. Pedrosa, 2020, ECML/PKDD.

Author Correction: Automatic diagnosis of the 12-lead ECG using a deep neural network

Manoel Horta Ribeiro, Antônio H. Ribeiro, Gabriela M. M. Paixão, 2020, Nature Communications.

Automatic Diagnosis of Short-Duration 12-Lead ECG using a Deep Convolutional Network pdf

Thomas B. Schön, Wagner Meira, Derick M. de Oliveira, 2018, ArXiv.

Neural network-derived electrocardiographic features have prognostic significance and important phenotypic and genotypic associations

D. O’Regan, J. Waks, K. Hnatkova, 2023, medRxiv.

Association Between Electrocardiographic Age and Cardiovascular Events in Community Settings: The Framingham Heart Study

J. Murabito, E. Benjamin, L. Brant, 2023, Circulation. Cardiovascular quality and outcomes.

Associação entre Bloqueio Atrioventricular e Mortalidade em Pacientes de Atenção Primária: O Estudo CODE

D. Oliveira, A. L. Ribeiro, Débora Oliveira, 2022, Arquivos brasileiros de cardiologia.