Gil Shamai
YOU?
Author Swipe
View article: Prediction of OncotypeDX recurrence score using H&E stained WSI images
Prediction of OncotypeDX recurrence score using H&E stained WSI images Open
The OncotypeDX 21-gene assay is a widely adopted tool for estimating recurrence risk and informing chemotherapy decisions in early-stage, hormone receptor-positive, HER2-negative breast cancer. Although informative, its high cost and long …
View article: Prediction of B/T Subtype and ETV6–RUNX1 Translocation in Pediatric Acute Lymphoblastic Leukemia by Deep Learning Analysis of Giemsa‐Stained Whole Slide Images of Bone Marrow Aspirates
Prediction of B/T Subtype and ETV6–RUNX1 Translocation in Pediatric Acute Lymphoblastic Leukemia by Deep Learning Analysis of Giemsa‐Stained Whole Slide Images of Bone Marrow Aspirates Open
Background Accurate determination of B/T‐cell lineage and the presence of the ETV6–RUNX1 translocation is critical for diagnosing acute lymphoblastic leukemia (ALL), as these factors influence treatment decisions and outcomes. However, the…
View article: Deep Learning on Histopathological Images to Predict Breast Cancer Recurrence Risk and Chemotherapy Benefit
Deep Learning on Histopathological Images to Predict Breast Cancer Recurrence Risk and Chemotherapy Benefit Open
Genomic testing has transformed treatment decisions for hormone receptor-positive, HER2-negative (HR+/HER2-) early breast cancer; however, it remains inaccessible to many patients worldwide due to high costs and logistical barriers. Here, …
View article: Artificial Intelligence Algorithms to Assess Hormonal Status From Tissue Microarrays in Patients With Breast Cancer
Artificial Intelligence Algorithms to Assess Hormonal Status From Tissue Microarrays in Patients With Breast Cancer Open
For at least half of the patients in this study, MBMP appeared to predict biomarker expression with noninferiority to IHC. Results suggest that prediction accuracy is likely to improve as data used for training expand. Morphological-based …
View article: Synthesizing facial photometries and corresponding geometries using generative adversarial networks
Synthesizing facial photometries and corresponding geometries using generative adversarial networks Open
Artificial data synthesis is currently a well studied topic with useful applications in data science, computer vision, graphics and many other fields. Generating realistic data is especially challenging since human perception is highly sen…
View article: High Quality Facial Surface and Texture Synthesis via Generative Adversarial Networks
High Quality Facial Surface and Texture Synthesis via Generative Adversarial Networks Open
In the past several decades, many attempts have been made to model synthetic realistic geometric data. The goal of such models is to generate plausible 3D geometries and textures. Perhaps the best known of its kind is the linear 3D morphab…
View article: An evaluation of canonical forms for non-rigid 3D shape retrieval
An evaluation of canonical forms for non-rigid 3D shape retrieval Open
Canonical forms attempt to factor out a non-rigid shape’s pose, giving a pose-neutral shape. This opens up the possibility of using methods originally designed for rigid shape retrieval for the task of non-rigid shape retrieval. We extend …
View article: Efficient Inter-Geodesic Distance Computation and Fast Classical Scaling
Efficient Inter-Geodesic Distance Computation and Fast Classical Scaling Open
Multidimensional scaling (MDS) is a dimensionality reduction tool used for information analysis, data visualization and manifold learning. Most MDS procedures embed data points in low-dimensional Euclidean (flat) domains, such that distanc…
View article: Fast Classical Scaling
Fast Classical Scaling Open
Multidimensional-scaling (MDS) is a dimensionality reduction tool used for information analysis, data visualization and manifold learning. Most MDS procedures find embedding of data points in low dimensional Euclidean (flat) domains, such …
View article: Geodesic Distance Descriptors
Geodesic Distance Descriptors Open
The Gromov-Hausdorff (GH) distance is traditionally used for measuring distances between metric spaces. It is defined as the minimal distortion of embedding one surface into the other, while the optimal correspondence can be described as t…