Yoel Shoshan

According to our database, Yoel Shoshan authored at least 14 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

MAMMAL - Molecular Aligned Multi-Modal Architecture and Language.

Yoel Shoshan, Moshiko Raboh, Michal Ozery-Flato, Vadim Ratner, Alex Golts, Jeffrey K. Weber, Ella Barkan, Simona Rabinovici-Cohen, Sagi Polaczek, Ido Amos, Ben Shapira, Liam Hazan, Matan Ninio, Sivan Ravid, Michael M. Danziger, Joseph A. Morrone, Parthasarathy Suryanarayanan, Michal Rosen-Zvi, Efrat Hexter

CoRR, 2024

A large dataset curation and benchmark for drug target interaction.

Alex Golts, Vadim Ratner, Yoel Shoshan, Moshe Raboh, Sagi Polaczek, Michal Ozery-Flato, Daniel Shats, Liam Hazan, Sivan Ravid, Efrat Hexter

CoRR, 2024

2023

FuseMedML: a framework for accelerated discovery in machine learning based biomedicine.

Alex Golts, Moshe Raboh, Yoel Shoshan, Sagi Polaczek, Simona Rabinovici-Cohen, Efrat Hexter

J. Open Source Softw., January, 2023

The KiTS21 Challenge: Automatic segmentation of kidneys, renal tumors, and renal cysts in corticomedullary-phase CT.

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

CoRR, 2023

2022

On the Choice of Active Site Sequences for Kinase-Ligand Affinity Prediction.

Jannis Born, Yoel Shoshan, Tien Huynh, Wendy D. Cornell, Eric J. Martin, Matteo Manica

J. Chem. Inf. Model., 2022

2021

Lessons from the first DBTex Challenge.

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

Nat. Mach. Intell., 2021

Beyond Non-maximum Suppression - Detecting Lesions in Digital Breast Tomosynthesis Volumes.

Yoel Shoshan, Aviad Zlotnick, Vadim Ratner, Daniel Khapun, Ella Barkan, Flora Gilboa-Solomon

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

An Ensemble of 3D U-Net Based Models for Segmentation of Kidney and Masses in CT Scans.

Alex Golts, Daniel Khapun, Daniel Shats, Yoel Shoshan, Flora Gilboa-Solomon

Proceedings of the Kidney and Kidney Tumor Segmentation - MICCAI 2021 Challenge, 2021

2020

The Case of Missed Cancers: Applying AI as a Radiologist's Safety Net.

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

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

2019

Mammogram Classification with Ordered Loss.

Rami Ben-Ari, Yoel Shoshan, Tal Tlusty

Proceedings of the Artificial Intelligence in Medicine, 2019

2018

Regularized adversarial examples for model interpretability.

Yoel Shoshan, Vadim Ratner

CoRR, 2018

Learning multiple non-mutually-exclusive tasks for improved classification of inherently ordered labels.

Vadim Ratner, Yoel Shoshan, Tal Kachman

CoRR, 2018

AdapterNet - learning input transformation for domain adaptation.

Alon Hazan, Yoel Shoshan, Daniel Khapun, Roy Aladjem, Vadim Ratner

CoRR, 2018

2017

Deep Learning for Automatic Detection of Abnormal Findings in Breast Mammography.

Ayelet Akselrod-Ballin, Leonid Karlinsky, Alon Hazan, Ran Bakalo, Ami Ben Horesh, Yoel Shoshan, Ella Barkan

Proceedings of the Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, 2017