Antônio L. P. Ribeiro
Orcid: 0000-0002-2740-0042Affiliations:
- Federal University of Minas Gerais, Belo Horizonte, MG, Brazil
According to our database1,
Antônio L. P. Ribeiro
authored at least 24 papers
between 2002 and 2024.
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Bibliography
2024
Artificial intelligence-enhanced electrocardiography derived body mass index as a predictor of future cardiometabolic disease.
npj Digit. Medicine, 2024
2023
Effect and usability of mobile health applications for medication adherence in patients with heart failure: A systematic review.
Int. J. Medical Informatics, October, 2023
On Merging Feature Engineering and Deep Learning for Diagnosis, Risk Prediction and Age Estimation Based on the 12-Lead ECG.
IEEE Trans. Biomed. Eng., July, 2023
End-to-end Risk Prediction of Atrial Fibrillation from the 12-Lead ECG by Deep Neural Networks.
CoRR, 2023
2022
Proceedings of the Computing in Cardiology, 2022
2021
Dataset, June, 2021
J. Inf. Data Manag., 2021
Towards automatic diagnosis of rheumatic heart disease on echocardiographic exams through video-based deep learning.
J. Am. Medical Informatics Assoc., 2021
2020
Commun. ACM, 2020
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track, 2020
Proceedings of the Computing in Cardiology, 2020
Proceedings of the Computing in Cardiology, 2020
2019
Automatic Diagnosis of the Short-Duration 12-Lead ECG using a Deep Neural Network: the CODE Study.
CoRR, 2019
Accuracy of Self-Reported Weight Collected Through a Web-Based Platform in a Weight Loss Trial: Validation Study of the POEmaS Clinical Trial.
Proceedings of the MEDINFO 2019: Health and Wellbeing e-Networks for All, 2019
Exploring the User Engagement Scale Short Form as a Determinant of Adherence in Digital Health Interventions.
Proceedings of the MEDINFO 2019: Health and Wellbeing e-Networks for All, 2019
Proceedings of the 9th International Conference on Cloud Computing and Services Science, 2019
2018
Automatic Diagnosis of Short-Duration 12-Lead ECG using a Deep Convolutional Network.
CoRR, 2018
2016
Symbolic features and classification via support vector machine for predicting death in patients with Chagas disease.
Comput. Biol. Medicine, 2016
2002
Comput. Biol. Medicine, 2002