Anees Kazi

Orcid: 0000-0003-4528-1670

According to our database1, Anees Kazi authored at least 31 papers between 2016 and 2024.

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

Timeline

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PhD thesis 
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On csauthors.net:

Bibliography

2024
On Discprecncies between Perturbation Evaluations of Graph Neural Network Attributions.
CoRR, 2024

2023
Unsupervised pre-training of graph transformers on patient population graphs.
Medical Image Anal., October, 2023

Graph-in-Graph (GiG): Learning interpretable latent graphs in non-Euclidean domain for biological and healthcare applications.
Medical Image Anal., August, 2023

Differentiable Graph Module (DGM) for Graph Convolutional Networks.
IEEE Trans. Pattern Anal. Mach. Intell., 2023

IA-GCN: Interpretable Attention Based Graph Convolutional Network for Disease Prediction.
Proceedings of the Machine Learning in Medical Imaging - 14th International Workshop, 2023

Multi-head Graph Convolutional Network for Structural Connectome Classification.
Proceedings of the Graphs in Biomedical Image Analysis, and Overlapped Cell on Tissue Dataset for Histopathology, 2023

Latent Graph Inference using Product Manifolds.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
RA-GCN: Graph convolutional network for disease prediction problems with imbalanced data.
Medical Image Anal., 2022

Graph-in-Graph (GiG): Learning interpretable latent graphs in non-Euclidean domain for biological and healthcare applications.
CoRR, 2022

Unsupervised Pre-Training on Patient Population Graphs for Patient-Level Predictions.
CoRR, 2022

DG-GRU: dynamic graph based gated recurrent unit for age and gender prediction using brain imaging.
Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, 2022

2021
IA-GCN: Interpretable Attention based Graph Convolutional Network for Disease prediction.
CoRR, 2021

Simultaneous imputation and classification using Multigraph Geometric Matrix Completion (MGMC): Application to neurodegenerative disease classification.
Artif. Intell. Medicine, 2021

GKD: Semi-supervised Graph Knowledge Distillation for Graph-Independent Inference.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

2020
Simultaneous imputation and disease classification in incomplete medical datasets using Multigraph Geometric Matrix Completion (MGMC).
CoRR, 2020

Latent Patient Network Learning for Automatic Diagnosis.
CoRR, 2020

Differentiable Graph Module (DGM) Graph Convolutional Networks.
CoRR, 2020

Precise proximal femur fracture classification for interactive training and surgical planning.
Int. J. Comput. Assist. Radiol. Surg., 2020

Latent-Graph Learning for Disease Prediction.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

2019
Multi-modal Graph Fusion for Inductive Disease Classification in Incomplete Datasets.
CoRR, 2019

Towards an Interactive and Interpretable CAD System to Support Proximal Femur Fracture Classification.
CoRR, 2019

Graph Convolution Based Attention Model for Personalized Disease Prediction.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

Adaptive Image-Feature Learning for Disease Classification Using Inductive Graph Networks.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

Self-Attention Equipped Graph Convolutions for Disease Prediction.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

InceptionGCN: Receptive Field Aware Graph Convolutional Network for Disease Prediction.
Proceedings of the Information Processing in Medical Imaging, 2019

2018
Weakly-Supervised Localization and Classification of Proximal Femur Fractures.
CoRR, 2018

Multi Layered-Parallel Graph Convolutional Network (ML-PGCN) for Disease Prediction.
CoRR, 2018

2017
Automatic Classification of Proximal Femur Fractures Based on Attention Models.
Proceedings of the Machine Learning in Medical Imaging - 8th International Workshop, 2017

Coupled Manifold Learning for Retrieval Across Modalities.
Proceedings of the 2017 IEEE International Conference on Computer Vision Workshops, 2017

2016
Metric hashing forests.
Medical Image Anal., 2016

Cross-Modal Manifold Learning for Cross-modal Retrieval.
CoRR, 2016


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