126 citations · 425 across the 72 of their papers we have counts for
14 papers · 1 filter
Continual Multiple Instance Learning for Hematologic Disease Diagnosis
Zahra Ebrahimi, Raheleh Salehi, Nassir Navab +2
The dynamic environment of laboratories and clinics, with streams of data arriving on a daily basis, requires regular updates of trained machine learning models for consistent perf…
Self-supervised Latent Space Optimization with Nebula Variational Coding
Yida Wang, David Joseph Tan, Nassir Navab +1
Deep learning approaches process data in a layer-by-layer way with intermediate (or latent) features. We aim at designing a general solution to optimize the latent manifolds to imp…
Graph-in-Graph (GiG): Learning interpretable latent graphs in non-Euclidean domain for biological and healthcare applications
Kamilia Mullakaeva, Luca Cosmo, Anees Kazi +3
Graphs are a powerful tool for representing and analyzing unstructured, non-Euclidean data ubiquitous in the healthcare domain. Two prominent examples are molecule property predict…
Do Explanations Explain? Model Knows Best
Ashkan Khakzar, Pedram Khorsandi, Rozhin Nobahari +1
It is a mystery which input features contribute to a neural network's output. Various explanation (feature attribution) methods are proposed in the literature to shed light on the…
Patient-specific virtual spine straightening and vertebra inpainting: An automatic framework for osteoplasty planning
Christina Bukas, Bailiang Jian, Luis F. Rodriguez Venegas +9
Symptomatic spinal vertebral compression fractures (VCFs) often require osteoplasty treatment. A cement-like material is injected into the bone to stabilize the fracture, restore t…
RA-GCN: Graph Convolutional Network for Disease Prediction Problems with Imbalanced Data
Mahsa Ghorbani, Anees Kazi, Mahdieh Soleymani Baghshah +2
Disease prediction is a well-known classification problem in medical applications. GCNs provide a powerful tool for analyzing the patients' features relative to each other. This ca…