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2020 – today
- 2024
[i5]Alex Golts, Vadim Ratner, Yoel Shoshan, Moshe Raboh, Sagi Polaczek, Michal Ozery-Flato, Daniel Shats, Liam Hazan, Sivan Ravid, Efrat Hexter:
A large dataset curation and benchmark for drug target interaction. CoRR abs/2401.17174 (2024)- 2023
- [j3]Alex Golts, Moshe Raboh, Yoel Shoshan, Sagi Polaczek, Simona Rabinovici-Cohen
, Efrat Hexter:
FuseMedML: a framework for accelerated discovery in machine learning based biomedicine. J. Open Source Softw. 8(81): 4943 (2023) - [i4]Nicholas Heller, Fabian Isensee, Dasha Trofimova, Resha Tejpaul, Zhongchen Zhao, Huai Chen, Lisheng Wang, Alex Golts, Daniel Khapun, Daniel Shats, Yoel Shoshan, Flora Gilboa-Solomon, Yasmeen George, Xi Yang, Jianpeng Zhang, Jing Zhang, Yong Xia, Mengran Wu, Zhiyang Liu, Edward Walczak, Seán McSweeney, Ranveer Vasdev, Chris Hornung, Rafat Solaiman, Jamee Schoephoerster, Bailey Abernathy, David Wu, Safa Abdulkadir, Ben Byun, Justice Spriggs, Griffin Struyk, Alexandra Austin, Ben Simpson, Michael Hagström, Sierra Virnig, John French, Nitin Venkatesh, Sarah Chan, Keenan Moore, Anna Jacobsen, Susan Austin, Mark Austin, Subodh Regmi, Nikolaos Papanikolopoulos, Christopher Weight:
The KiTS21 Challenge: Automatic segmentation of kidneys, renal tumors, and renal cysts in corticomedullary-phase CT. CoRR abs/2307.01984 (2023) - 2022
- [j2]Jannis Born, Yoel Shoshan, Tien Huynh, Wendy D. Cornell, Eric J. Martin, Matteo Manica:
On the Choice of Active Site Sequences for Kinase-Ligand Affinity Prediction. J. Chem. Inf. Model. 62(18): 4295-4299 (2022) - 2021
- [j1]Jungkyu Park, Yoel Shoshan, Robert Martí, Pablo Gómez del Campo, Vadim Ratner, Daniel Khapun, Aviad Zlotnick, Ella Barkan, Flora Gilboa-Solomon, Jakub Chledowski, Jan Witowski, Alexandra Millet, Eric Kim, Alana Lewin, Kristine Pysarenko, Sardius Chen, Julia Goldberg, Shalin Patel, Anastasia Plaunova, Melanie Wegener, Stacey Wolfson, Jiyon Lee, Sana Hava, Sindhoora Murthy, Linda Du, Sushma Gaddam, Ujas Parikh, Laura Heacock, Linda Moy, Beatriu Reig, Michal Rosen-Zvi, Krzysztof J. Geras:
Lessons from the first DBTex Challenge. Nat. Mach. Intell. 3(8): 735-736 (2021) - [c5]Alex Golts, Daniel Khapun, Daniel Shats, Yoel Shoshan, Flora Gilboa-Solomon:
An Ensemble of 3D U-Net Based Models for Segmentation of Kidney and Masses in CT Scans. KiTS@MICCAI 2021: 103-115 - [c4]Yoel Shoshan, Aviad Zlotnick, Vadim Ratner, Daniel Khapun, Ella Barkan, Flora Gilboa-Solomon:
Beyond Non-maximum Suppression - Detecting Lesions in Digital Breast Tomosynthesis Volumes. MICCAI (5) 2021: 772-781 - 2020
- [c3]Michal Chorev, Yoel Shoshan, Ayelet Akselrod-Ballin, Adam Spiro, Shaked Naor, Alon Hazan, Vesna Resende Barros, Iuliana Weinstein, Esma Herzel, Varda Shalev, Michal Guindy, Michal Rosen-Zvi:
The Case of Missed Cancers: Applying AI as a Radiologist's Safety Net. MICCAI (6) 2020: 220-229
2010 – 2019
- 2019
- [c2]Rami Ben-Ari, Yoel Shoshan, Tal Tlusty:
Mammogram Classification with Ordered Loss. AIME 2019: 67-76 - 2018
- [i3]Alon Hazan, Yoel Shoshan, Daniel Khapun, Roy Aladjem, Vadim Ratner:
AdapterNet - learning input transformation for domain adaptation. CoRR abs/1805.11601 (2018) - [i2]Vadim Ratner, Yoel Shoshan, Tal Kachman:
Learning multiple non-mutually-exclusive tasks for improved classification of inherently ordered labels. CoRR abs/1805.11837 (2018) - [i1]Yoel Shoshan, Vadim Ratner:
Regularized adversarial examples for model interpretability. CoRR abs/1811.07311 (2018) - 2017
- [c1]Ayelet Akselrod-Ballin, Leonid Karlinsky, Alon Hazan, Ran Bakalo, Ami Ben Horesh, Yoel Shoshan, Ella Barkan:
Deep Learning for Automatic Detection of Abnormal Findings in Breast Mammography. DLMIA/ML-CDS@MICCAI 2017: 321-329
Coauthor Index
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last updated on 2024-10-07 21:23 CEST by the dblp team
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