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Gil Shamai

Showing results (1-10 of 10) with videos related to

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IEEE Transactions on Pattern Analysis and Machine Intelligence|October 30, 2018
Efficient Inter-Geodesic Distance Computation and Fast Classical ScalingGil Shamai, Michael Zibulevsky, Ron Kimmel
The Lancet. Oncology|June 29, 2026
The intermediate-risk gap in AI-based breast cancer stratification - Authors' replyGil Shamai, Ron Kimmel, Dvir Aran
JAMA Network Open|July 27, 2019
Artificial Intelligence Algorithms to Assess Hormonal Status From Tissue Microarrays in Patients With Breast CancerGil Shamai, Yoav Binenbaum, Ron Slossberg, et al.
Nature Communications|November 8, 2022
Deep learning-based image analysis predicts PD-L1 status from H&E-stained histopathology images in breast cancerGil Shamai, Amir Livne, António Polónia, et al.
Pediatric Blood & Cancer|May 21, 2025
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 AspiratesArkadi Piven, Gil Shamai, Sarah Elitzur, et al.
Communications Medicine|December 20, 2024
Clinical utility of receptor status prediction in breast cancer and misdiagnosis identification using deep learning on hematoxylin and eosin-stained slidesGil Shamai, Ran Schley, Alexandra Cretu, et al.
NPJ Breast Cancer|May 11, 2026
Prediction of OncotypeDX recurrence score using hematoxylin and eosin-stained whole slide imagesShachar Cohen, Gil Shamai, Edmond Sabo, et al.
Medrxiv : the Preprint Server for Health Sciences|July 15, 2025
Deep Learning on Histopathological Images to Predict Breast Cancer Recurrence Risk and Chemotherapy BenefitGil Shamai, Shachar Cohen, Yoav Binenbaum, et al.
The Lancet. Oncology|March 14, 2026
Deep learning on histopathological images to predict breast cancer recurrence risk and chemotherapy benefit: a multicentre, model development and validation studyGil Shamai, Shachar Cohen, Yoav Binenbaum, et al.
Medrxiv : the Preprint Server for Health Sciences|May 25, 2026
Development and Validation of a Multimodal Clinical, Pathologic, and Genomic Model for Breast Cancer RecurrenceNgoc-Kim Nguyen, Anran Li, Sara Kochanny, et al.
Pageof 1

Showing results (1-10 of 10) with videos related to

Sort By:
Pageof 1
IEEE Transactions on Pattern Analysis and Machine Intelligence|October 30, 2018
Efficient Inter-Geodesic Distance Computation and Fast Classical ScalingGil Shamai, Michael Zibulevsky, Ron Kimmel
The Lancet. Oncology|June 29, 2026
The intermediate-risk gap in AI-based breast cancer stratification - Authors' replyGil Shamai, Ron Kimmel, Dvir Aran
JAMA Network Open|July 27, 2019
Artificial Intelligence Algorithms to Assess Hormonal Status From Tissue Microarrays in Patients With Breast CancerGil Shamai, Yoav Binenbaum, Ron Slossberg, et al.
Nature Communications|November 8, 2022
Deep learning-based image analysis predicts PD-L1 status from H&E-stained histopathology images in breast cancerGil Shamai, Amir Livne, António Polónia, et al.
Pediatric Blood & Cancer|May 21, 2025
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 AspiratesArkadi Piven, Gil Shamai, Sarah Elitzur, et al.
Communications Medicine|December 20, 2024
Clinical utility of receptor status prediction in breast cancer and misdiagnosis identification using deep learning on hematoxylin and eosin-stained slidesGil Shamai, Ran Schley, Alexandra Cretu, et al.
NPJ Breast Cancer|May 11, 2026
Prediction of OncotypeDX recurrence score using hematoxylin and eosin-stained whole slide imagesShachar Cohen, Gil Shamai, Edmond Sabo, et al.
Medrxiv : the Preprint Server for Health Sciences|July 15, 2025
Deep Learning on Histopathological Images to Predict Breast Cancer Recurrence Risk and Chemotherapy BenefitGil Shamai, Shachar Cohen, Yoav Binenbaum, et al.
The Lancet. Oncology|March 14, 2026
Deep learning on histopathological images to predict breast cancer recurrence risk and chemotherapy benefit: a multicentre, model development and validation studyGil Shamai, Shachar Cohen, Yoav Binenbaum, et al.
Medrxiv : the Preprint Server for Health Sciences|May 25, 2026
Development and Validation of a Multimodal Clinical, Pathologic, and Genomic Model for Breast Cancer RecurrenceNgoc-Kim Nguyen, Anran Li, Sara Kochanny, et al.
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