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A machine-learning sleep-wake classification model using a reduced number of features derived from photoplethysmography and activity signals.

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A machine-learning sleep-wake classification model using a reduced number of features derived from photoplethysmography and activity signals., , , , , , , and . CoRR, (2023)Blood Pressure Estimation From Photoplethysmography by Considering Intra- and Inter-Subject Variabilities: Guidelines for a Fair Assessment., , , , , , and . IEEE Access, (2023)Exploring the limitations of blood pressure estimation using the photoplethysmography signal., , , , , , and . CoRR, (2024)Novel Chest Radiographic Biomarkers for COVID-19 Using Radiomic Features Associated with Diagnostics and Outcomes., , , , , and . J. Digit. Imaging, 34 (2): 297-307 (2021)Automated radiographic bone suppression with deep convolutional neural networks., , , , , and . Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging, volume 11600 of SPIE Proceedings, SPIE, (2021)Quality Assessment of Photoplethysmography Signals For Cardiovascular Biomarkers Monitoring Using Wearable Devices., , , , , , , and . CoRR, (2023)A Machine Learning Approach to Predict Arterial Blood Pressure from Photoplethysmography Signal., , , , , and . CinC, page 1-4. IEEE, (2022)A deep learning approach for COVID-19 screening and localization on chest x-ray images., , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 12033 of SPIE Proceedings, SPIE, (2022)Automatic Stent Segmentation in IOCT images Using Combined Feature Extraction Techniques and Mathematical Morphology., , and . CinC, page 1215-1218. www.cinc.org, (2013)Machine Learning-Based Diabetes Detection Using Photoplethysmography Signal Features., , , , , , , and . CoRR, (2023)