José Eduardo Krieger
Orcid: 0000-0001-5464-1792
According to our database1,
José Eduardo Krieger authored at least 27 papers
between 2019 and 2025.
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Bibliography
2025
Non-invasive Blood Glucose Estimation: an Approach Using Multi-Wavelength PPG Signals and Residual Neural Networks.
Proceedings of the 21st International Symposium on Biomedical Image Processing and Analysis, 2025
Enhancing Privacy in Clinical Texts: A New Approach to De-Identification of Brazilian Clinical Narratives.
Proceedings of the MEDINFO 2025 - Healthcare Smart × Medicine Deep, 2025
Architectural Framework for Developing a Healthcare Research Data Repository: A Scalable and Interoperable Approach.
Proceedings of the MEDINFO 2025 - Healthcare Smart × Medicine Deep, 2025
Enhancing Photoplethysmography-Based Sleep Staging Models Through Temporal Context Optimization.
Proceedings of the MEDINFO 2025 - Healthcare Smart × Medicine Deep, 2025
2024
Optimizing Photoplethysmography-Based Sleep Staging Models by Leveraging Temporal Context for Wearable Devices Applications.
CoRR, 2024
Exploring the limitations of blood pressure estimation using the photoplethysmography signal.
CoRR, 2024
2023
Frontiers Bioinform., May, 2023
A machine-learning sleep-wake classification model using a reduced number of features derived from photoplethysmography and activity signals.
CoRR, 2023
Machine Learning-Based Diabetes Detection Using Photoplethysmography Signal Features.
CoRR, 2023
Quality Assessment of Photoplethysmography Signals For Cardiovascular Biomarkers Monitoring Using Wearable Devices.
CoRR, 2023
Artificial Intelligence-Driven Screening System for Rapid Image-Based Classification of 12-Lead ECG Exams: A Promising Solution for Emergency Room Prioritization.
IEEE Access, 2023
Blood Pressure Estimation From Photoplethysmography by Considering Intra- and Inter-Subject Variabilities: Guidelines for a Fair Assessment.
IEEE Access, 2023
Automatic segmentation of stroke lesions in T1-weighted magnetic resonance images with convolutional neural networks.
Proceedings of the Medical Imaging 2023: Computer-Aided Diagnosis, San Diego, 2023
Developing a Machine Learning Pipeline for Predicting Neurological Outcomes in Comatose Cardiac Arrest Survivors Using Continuous EEG Data.
Proceedings of the Computing in Cardiology, 2023
CardioBERTpt: Transformer-based Models for Cardiology Language Representation in Portuguese.
Proceedings of the 36th IEEE International Symposium on Computer-Based Medical Systems, 2023
2022
Proceedings of the Symposium on Internet of Things, 2022
A deep learning approach for COVID-19 screening and localization on chest x-ray images.
Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, San Diego, 2022
A Machine Learning Approach to Predict Arterial Blood Pressure from Photoplethysmography Signal.
Proceedings of the Computing in Cardiology, 2022
2021
SN Comput. Sci., 2021
Novel Chest Radiographic Biomarkers for COVID-19 Using Radiomic Features Associated with Diagnostics and Outcomes.
J. Digit. Imaging, 2021
CoRR, 2021
A general fully automated deep-learning method to detect cardiomegaly in chest x-rays.
Proceedings of the Medical Imaging 2021: Computer-Aided Diagnosis, 2021
Proceedings of the Medical Imaging 2021: Biomedical Applications in Molecular, 2021
Proceedings of the Computing in Cardiology, CinC 2021, Brno, 2021
2020
Fully Automated Quantification of Cardiac Indices from Cine MRI Using a Combination of Convolution Neural Networks.
Proceedings of the 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2020
Multi-View Ensemble Convolutional Neural Network to Improve Classification of Pneumonia in Low Contrast Chest X-Ray Images.
Proceedings of the 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2020
2019
J. Chem. Inf. Model., 2019