Our team at Zebra is tackling some of the most complex and interesting problems in the global health care space. We are employing a robust mix of data science, research and collaboration to achieve game changing results never thought possible before. We are fearlessly pushing the boundaries on teaching computers to learn and interpret medical data and images, with outcomes that are truly disruptive and that have significant implications on a global scale for all stakeholders including patients, providers and payors.

TextRay: Mining Clinical Reports To Gain A Broad Understanding Of Chest X-Rays (Poster)

Authors:

Jonathan Laserson, Christine Dan Lantsman, Michal Cohen-Sfady, Itamar Tamir, Eli Goz, Chen Brestel, Shir Bar, Maya Atar, Eldad Elnekave, Zebra Medical Vision

Presented at:

MICCAI 2018

Date:

September 2018

 

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Improved Intracranial Hemorrhage Classification using Deep Multi-task Learning

Authors:

Amir Bar, MS, Zebra Medical Vision, Inc.; Michal Mauda, MD, PhD; Yoni Turner, MD; Michal Cohen-Sfady, PhD;
Eldad Elnekave, MD

Presented at:

2018 SIIM Conference on Machine Intelligence in Medical Imaging

Date:

September 2018



RadBot-CXR: Classification of Four Clinical Finding Categories in Chest X-Ray Using Deep Learning (Poster)

Authors:

Chen Brestel, Ran Shadmi, Itamar Tamir, Michal Cohen-Sfaty, Eldad Elnekave

Presented at:

MIDL 2018 Conference

Date:

July 2018

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Malignancy Detection on Mammography Using Dual Deep Convolutional Neural Networks and Genetically Discovered False Color Input Enhancement

Authors:

Philip TeareMichael FishmanOshra BenzaquenEyal ToledanoEldad Elnekave

Published in:

Journal of Digital Imaging, Volume 30, Issue 4

Date:

August 2018



Computing DEXA Score from CT Using Deep Segmentation Networks Cascade

Authors:

Orna B. Amitai, MS, Zebra Medical Vision; Amir Bar, MS, Zebra Medical Vision; Eyal Toledano, MS, Zebra Medical Vision; Eldad Elnekave, MD, Zebra Medical Vision

Presented at:

2nd SIIM Conference on Machine Intelligence in Medical Imaging

Date:

September 2017



Language Generation with Recurrent Generative Adversarial Networks without Pre-training

Authors:

Ofir Press, Amir Bar, Ben Bogin, Jonathan Berant, Lior Wolf

Published in:

arxiv.org

Date:

June 2017



Compression fractures detection on CT

Authors:

Amir Bar, Lior Wolf, Orna Bergman Amitai, Eyal Toledano, and Eldad Elnekave, The Blavatnik School of Computer Science, Tel Aviv University, Zebra Medical Vision

Published in:

Spie digital library

Date:

2017



 

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