Kyriaki-Margarita Bintsi

According to our database1, Kyriaki-Margarita Bintsi authored at least 11 papers between 2020 and 2024.

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

Timeline

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Links

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Bibliography

2024
Are Population Graphs Really as Powerful as Believed?
Trans. Mach. Learn. Res., 2024

A Survey on Graph Construction for Geometric Deep Learning in Medicine: Methods and Recommendations.
Trans. Mach. Learn. Res., 2024

2023
Extended Graph Assessment Metrics for Graph Neural Networks.
CoRR, 2023

Extended Graph Assessment Metrics for Regression and Weighted Graphs.
Proceedings of the Graphs in Biomedical Image Analysis, and Overlapped Cell on Tissue Dataset for Histopathology, 2023

A Comparative Study of Population-Graph Construction Methods and Graph Neural Networks for Brain Age Regression.
Proceedings of the Graphs in Biomedical Image Analysis, and Overlapped Cell on Tissue Dataset for Histopathology, 2023

Multimodal Brain Age Estimation Using Interpretable Adaptive Population-Graph Learning.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

2022
GraphWalks: Efficient Shape Agnostic Geodesic Shortest Path Estimation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021
Voxel-Level Importance Maps for Interpretable Brain Age Estimation.
Proceedings of the Interpretability of Machine Intelligence in Medical Image Computing, and Topological Data Analysis and Its Applications for Medical Data, 2021

The Effect of the Loss on Generalization: Empirical Study on Synthetic Lung Nodule Data.
Proceedings of the Interpretability of Machine Intelligence in Medical Image Computing, and Topological Data Analysis and Its Applications for Medical Data, 2021

The Pitfalls of Sample Selection: A Case Study on Lung Nodule Classification.
Proceedings of the Predictive Intelligence in Medicine - 4th International Workshop, 2021

2020
Patch-Based Brain Age Estimation from MR Images.
Proceedings of the Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology, 2020


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