Ramon Correa

According to our database1, Ramon Correa authored at least 12 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Efficient adversarial debiasing with concept activation vector - Medical image case-studies.
J. Biomed. Informatics, January, 2024

2022
The EMory BrEast imaging Dataset (EMBED): A Racially Diverse, Granular Dataset of 3.5M Screening and Diagnostic Mammograms.
CoRR, 2022

Networking Research Innovations for Telesurgery: A Systematic Review.
Proceedings of the Ninth International Conference on Software Defined Systems, 2022

A radiomics approach to distinguish non-contrast enhancing tumor from vasogenic edema on multi-parametric pre-treatment MRI scans for glioblastoma tumors.
Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, 2022

2021
Two-step adversarial debiasing with partial learning - medical image case-studies.
CoRR, 2021

Reading Race: AI Recognises Patient's Racial Identity In Medical Images.
CoRR, 2021

2020
Can Tumor Location on Pre-treatment MRI Predict Likelihood of Pseudo-Progression vs. Tumor Recurrence in Glioblastoma? - A Feasibility Study.
Frontiers Comput. Neurosci., 2020

Can tumor location on pre-treatment MRI predict likelihood of pseudo-progression versus tumor recurrence in Glioblastoma? A feasibility study.
CoRR, 2020

Spatial-And-Context Aware (SpACe) "Virtual Biopsy" Radiogenomic Maps to Target Tumor Mutational Status on Structural MRI.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

"Lesion-habitat" radiomics to distinguish radiation necrosis from tumor recurrence on post-treatment MRI in metastatic brain tumors.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020

2019
Radiomics of the lesion habitat on pre-treatment MRI predicts response to chemo-radiation therapy in Glioblastoma.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, 2019

Deformation heterogeneity radiomics to predict molecular subtypes of pediatric Medulloblastoma on routine MRI.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, 2019


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