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07/13/2023
MaxCorrMGNN: A Multi-Graph Neural Network Framework for Generalized Multimodal Fusion of Medical Data for Outcome Prediction
With the emergence of multimodal electronic health records, the evidence...
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10/25/2022
Fusing Modalities by Multiplexed Graph Neural Networks for Outcome Prediction in Tuberculosis
In a complex disease such as tuberculosis, the evidence for the disease ...
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03/04/2021
Learning Whole-Slide Segmentation from Inexact and Incomplete Labels using Tissue Graphs
Segmenting histology images into diagnostically relevant regions is impe...
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11/25/2020
Quantifying Explainers of Graph Neural Networks in Computational Pathology
Explainability of deep learning methods is imperative to facilitate thei...
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07/02/2020
Learning-based Defect Recognition for Quasi-Periodic Microscope Images
The detailed control of crystalline material defects is a crucial proces...
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07/01/2020
Towards Explainable Graph Representations in Digital Pathology
Explainability of machine learning (ML) techniques in digital pathology ...
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06/24/2020
NINEPINS: Nuclei Instance Segmentation with Point Annotations
Deep learning-based methods are gaining traction in digital pathology, w...
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06/17/2020
Mitosis Detection Under Limited Annotation: A Joint Learning Approach
Mitotic counting is a vital prognostic marker of tumor proliferation in ...
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03/16/2017