Automatic Stent Segmentation in IOCT images Using Combined Feature Extraction Techniques and Mathematical Morphology. - Matheus Cardoso Moraes; Diego Armando Cardona Cárdenas; Sérgio Shiguemi Furuie (CinC, 2013)

Multi-View Ensemble Convolutional Neural Network to Improve Classification of Pneumonia in Low Contrast Chest X-Ray Images. - José Raniery Ferreira; Diego Armando Cardona Cárdenas; Ramon Alfredo Moreno; Marina de Sá Rebelo; José Eduardo Krieger; Marco Antonio Gutierrez 001 (EMBC, 2020)

Automated radiographic bone suppression with deep convolutional neural networks. - Diego Armando Cardona Cárdenas; José Raniery Ferreira Jr.; Ramon Alfredo Moreno; Marina de Fátima de Sá Rebelo; José Eduardo Krieger; Marco A. Gutierrez 001 (Biomedical Applications in Molecular, Structural, and Functional Imaging, 2021)

A general fully automated deep-learning method to detect cardiomegaly in chest x-rays. - José Raniery Ferreira Jr.; Diego Armando Cardona Cárdenas; Ramon Alfredo Moreno; Marina de Fátima de Sá Rebelo; José Eduardo Krieger; Marco Antonio Gutierrez 001 (Computer-Aided Diagnosis, 2021)

Complementary use of priors for pulmonary imaging with electrical impedance and ultrasound computed tomography. - Melody Alsaker; Diego Armando Cardona Cárdenas; Sérgio Shiguemi Furuie; Jennifer L. Mueller (J. Comput. Appl. Math., 2021)

Novel Chest Radiographic Biomarkers for COVID-19 Using Radiomic Features Associated with Diagnostics and Outcomes. - José Raniery Ferreira Jr.; Diego Armando Cardona Cárdenas; Ramon Alfredo Moreno; Marina de Sá Rebelo; José Eduardo Krieger; Marco Antonio Gutierrez 001 (J. Digit. Imaging, 2021)

A Machine Learning Approach to Predict Arterial Blood Pressure from Photoplethysmography Signal. - Felipe Meneguitti Dias; Thiago Bulhões da Silva Costa; Diego Armando Cardona Cárdenas; Marcelo Toledo; José Eduardo Krieger; Marco A. Gutierrez 001 (CinC, 2022)

A deep learning approach for COVID-19 screening and localization on chest x-ray images. - Karem Daiane Marcomini; Diego Armando Cardona Cárdenas; Agma Juci Machado Traina; José Eduardo Krieger; Marco Antonio Gutierrez 001 (Computer-Aided Diagnosis, 2022)

Blood Pressure Estimation From Photoplethysmography by Considering Intra- and Inter-Subject Variabilities: Guidelines for a Fair Assessment. - Thiago Bulhões da Silva Costa; Felipe Meneguitti Dias; Diego Armando Cardona Cárdenas; Marcelo Toledo; Daniel Mario de Lima; José Eduardo Krieger; Marco Antonio Gutierrez 001 (IEEE Access, 2023)

Quality Assessment of Photoplethysmography Signals For Cardiovascular Biomarkers Monitoring Using Wearable Devices. - Felipe Meneguitti Dias; Marcelo A. F. Toledo; Diego Armando Cardona Cárdenas; Douglas A. Almeida; Filipe A. C. Oliveira; Estela Ribeiro; José Eduardo Krieger; Marco A. Gutierrez 001 (CoRR, 2023)

Machine Learning-Based Diabetes Detection Using Photoplethysmography Signal Features. - Filipe A. C. Oliveira; Felipe Meneguitti Dias; Marcelo A. F. Toledo; Diego Armando Cardona Cárdenas; Douglas A. Almeida; Estela Ribeiro; José Eduardo Krieger; Marco A. Gutierrez 001 (CoRR, 2023)

A machine-learning sleep-wake classification model using a reduced number of features derived from photoplethysmography and activity signals. - Douglas A. Almeida; Felipe Meneguitti Dias; Marcelo A. F. Toledo; Diego Armando Cardona Cárdenas; Filipe A. C. Oliveira; Estela Ribeiro; José Eduardo Krieger; Marco A. Gutierrez 001 (CoRR, 2023)

Exploring the limitations of blood pressure estimation using the photoplethysmography signal. - Felipe Meneguitti Dias; Diego Armando Cardona Cárdenas; Marcelo A. F. Toledo; Filipe A. C. Oliveira; Estela Ribeiro; José Eduardo Krieger; Marco A. Gutierrez 001 (CoRR, 2024)