Area of research
Cognitive Neuroscience · Signal Processing
Research interest
Research interests include EEG and Brain-Computer Interfaces, Blind Source Separation Techniques, Neural Networks and Applications, and Neural dynamics and brain function.
Genome-wide association identifies novel ROP risk loci in a multiethnic cohort
Improving the study of brain-behavior relationships by revisiting basic assumptions
Association of Biomarker-Based Artificial Intelligence With Risk of Racial Bias in Retinal Images
Discrepancies in Diagnosis of Treatment-Requiring Retinopathy of Prematurity
Federated Learning for Multicenter Collaboration in Ophthalmology
Federated Learning for Multicenter Collaboration in Ophthalmology
EEG-GAT: Graph Attention Networks for Classification of Electroencephalogram (EEG) Signals
Variability in Plus Disease Diagnosis using Single and Serial Images
Single-Examination Risk Prediction of Severe Retinopathy of Prematurity
Identification of candidate genes and pathways in retinopathy of prematurity by whole exome sequencing of preterm infants enriched in phenotypic extremes
Evaluation of a Deep Learning–Derived Quantitative Retinopathy of Prematurity Severity Scale
Plus Disease in Retinopathy of Prematurity: Convolutional Neural Network Performance Using a Combined Neural Network and Feature Extraction Approach
Variability in Plus Disease Identified Using a Deep Learning-Based Retinopathy of Prematurity Severity Scale
Monitoring Disease Progression With a Quantitative Severity Scale for Retinopathy of Prematurity Using Deep Learning
A Quantitative Severity Scale for Retinopathy of Prematurity Using Deep Learning to Monitor Disease Regression After Treatment
Automated Fundus Image Quality Assessment in Retinopathy of Prematurity Using Deep Convolutional Neural Networks
Automated Diagnosis of Plus Disease in Retinopathy of Prematurity Using Deep Convolutional Neural Networks
Evaluation of a deep learning image assessment system for detecting severe retinopathy of prematurity
Fully automated disease severity assessment and treatment monitoring in retinopathy of prematurity using deep learning
Assessment of a Tele-education System to Enhance Retinopathy of Prematurity Training by International Ophthalmologists-in-Training in Mexico
Plus Disease in Retinopathy of Prematurity: Diagnostic Trends in 2016 Versus 2007
Expert Diagnosis of Plus Disease in Retinopathy of Prematurity From Computer-Based Image Analysis
Optimization of focality and direction in dense electrode array transcranial direct current stimulation (tDCS)
Plus Disease in Retinopathy of Prematurity
Plus Disease in Retinopathy of Prematurity
Computer-Based Image Analysis for Plus Disease Diagnosis in Retinopathy of Prematurity: Performance of the “i-ROP” System and Image Features Associated With Expert Diagnosis
Retinal vasculature segmentation using principal spanning forests