Search Results for author: Eldad Elnekave

Found 4 papers, 0 papers with code

Improved ICH classification using task-dependent learning

no code implementations29 Jun 2019 Amir Bar, Michal Mauda, Yoni Turner, Michal Safadi, Eldad Elnekave

Head CT is one of the most commonly performed imaging studied in the Emergency Department setting and Intracranial hemorrhage (ICH) is among the most critical and timesensitive findings to be detected on Head CT. We present BloodNet, a deep learning architecture designed for optimal triaging of Head CTs, with the goal of decreasing the time from CT acquisition to accurate ICH detection.

Classification General Classification

PHT-bot: Deep-Learning based system for automatic risk stratification of COPD patients based upon signs of Pulmonary Hypertension

no code implementations28 May 2019 David Chettrit, Orna Bregman Amitai, Itamar Tamir, Amir Bar, Eldad Elnekave

Secondary pulmonary hypertension is a manifestation of advanced COPD, which can be reliably diagnosed by the main Pulmonary Artery (PA) to Ascending Aorta (Ao) ratio.

Computed Tomography (CT)

TextRay: Mining Clinical Reports to Gain a Broad Understanding of Chest X-rays

no code implementations6 Jun 2018 Jonathan Laserson, Christine Dan Lantsman, Michal Cohen-Sfady, Itamar Tamir, Eli Goz, Chen Brestel, Shir Bar, Maya Atar, Eldad Elnekave

The chest X-ray (CXR) is by far the most commonly performed radiological examination for screening and diagnosis of many cardiac and pulmonary diseases.

Compression Fractures Detection on CT

no code implementations6 Jun 2017 Amir Bar, Lior Wolf, Orna Bergman Amitai, Eyal Toledano, Eldad Elnekave

Finally a Recurrent Neural Network (RNN) is utilized to predict whether a vertebral fracture is present in the series of patches.

Computed Tomography (CT)

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