Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Yoel Shoshan"'
Autor:
Yoel Shoshan, Ran Bakalo, Flora Gilboa-Solomon, Vadim Ratner, Ella Barkan, Michal Ozery-Flato, Mika Amit, Daniel Khapun, Emily B. Ambinder, Eniola T. Oluyemi, Babita Panigrahi, Philip A. DiCarlo, Michal Rosen-Zvi, Lisa A. Mullen
Publikováno v:
Radiology. 303:69-77
Background Digital breast tomosynthesis (DBT) has higher diagnostic accuracy than digital mammography, but interpretation time is substantially longer. Artificial intelligence (AI) could improve reading efficiency. Purpose To evaluate the use of AI t
Publikováno v:
Journal of Chemical Information and Modeling, 62 (18)
Recent work showed that active site rather than full-protein-sequence information improves predictive performance in kinase-ligand binding affinity prediction. To refine the notion of an "active site", we here propose and compare multiple definitions
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fdef3353765b303aa96fefe6e7ec6f4c
https://hdl.handle.net/20.500.11850/575018
https://hdl.handle.net/20.500.11850/575018
Autor:
Nicholas Konz, Mateusz Buda, Hanxue Gu, Ashirbani Saha, Jichen Yang, Jakub Chłędowski, Jungkyu Park, Jan Witowski, Krzysztof J. Geras, Yoel Shoshan, Flora Gilboa-Solomon, Daniel Khapun, Vadim Ratner, Ella Barkan, Michal Ozery-Flato, Robert Martí, Akinyinka Omigbodun, Chrysostomos Marasinou, Noor Nakhaei, William Hsu, Pranjal Sahu, Md Belayat Hossain, Juhun Lee, Carlos Santos, Artur Przelaskowski, Jayashree Kalpathy-Cramer, Benjamin Bearce, Kenny Cha, Keyvan Farahani, Nicholas Petrick, Lubomir Hadjiiski, Karen Drukker, Samuel G. Armato, Maciej A. Mazurowski
Publikováno v:
JAMA Network Open. 6:e230524
ImportanceAn accurate and robust artificial intelligence (AI) algorithm for detecting cancer in digital breast tomosynthesis (DBT) could significantly improve detection accuracy and reduce health care costs worldwide.ObjectivesTo make training and ev
Publikováno v:
Journal of Open Source Software. 8:4943
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030983840
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::274985da047a6473e5e59cf4a2ebb7ae
https://doi.org/10.1007/978-3-030-98385-7_14
https://doi.org/10.1007/978-3-030-98385-7_14
Autor:
Roie Melamed, Alon Hazan, Esma Herzel, Shaked Naor, Gideon Koren, Ayelet Akselrod-Ballin, Yaara Goldschmidt, Michal Rosen-Zvi, Michal Chorev, Adam Spiro, Ehud Karavani, Yoel Shoshan, Michal Guindy, Varda Shalev, Ella Barkan
Publikováno v:
Radiology. 292:331-342
Background Computational models on the basis of deep neural networks are increasingly used to analyze health care data. However, the efficacy of traditional computational models in radiology is a matter of debate. Purpose To evaluate the accuracy and
Publikováno v:
Medical Image Computing and Computer Assisted Intervention – MICCAI 2021 ISBN: 9783030872397
MICCAI (5)
MICCAI (5)
Detecting the specific locations of malignancy signs in a medical image is a non-trivial and time-consuming task for radiologists. A complex, 3D version of this task, was presented in the DBTex 2021 Grand Challenge on Digital Breast Tomosynthesis Les
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fa6866820441369f3fe60ddf1a78f3ac
https://doi.org/10.1007/978-3-030-87240-3_74
https://doi.org/10.1007/978-3-030-87240-3_74
Autor:
Kristine Pysarenko, Pablo Gómez del Campo, Daniel Khapun, Alana A. Lewin, Linda Moy, Jungkyu Park, Yoel Shoshan, Sindhoora Murthy, Julia E. Goldberg, Robert Martí, Ella Barkan, Linda Du, Jakub Chłędowski, Ujas Parikh, Anastasia Plaunova, Krzysztof J. Geras, Sardius Chen, Alexandra Millet, Laura Heacock, Sushma Gaddam, Melanie Wegener, Eric H. Kim, Vadim Ratner, Beatriu Reig, Shalin Patel, Sana Hava, Jan Witowski, Stacey Wolfson, Michal Rosen-Zvi, Aviad Zlotnick, Jiyon Lee, Flora Gilboa-Solomon
Publikováno v:
Nature Machine Intelligence. 3:735-736
A new international competition aims to speed up the development of AI models that can assist radiologists in detecting suspicious lesions from hundreds of millions of pixels in 3D mammograms. The top three winning teams compare notes.
Autor:
Adam Spiro, Esma Herzel, Shaked Naor, Ayelet Akselrod-Ballin, Varda Shalev, Michal Guindy, Alon Hazan, Vesna Resende Barros, Iuliana Weinstein, Michal Chorev, Michal Rosen-Zvi, Yoel Shoshan
Publikováno v:
Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 ISBN: 9783030597245
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::610b7d8f1153839f54bacd0ee23a61d7
https://doi.org/10.1007/978-3-030-59725-2_79
https://doi.org/10.1007/978-3-030-59725-2_79
Autor:
Michal Chorev, Iuliana Weinstein, Michal Guindy, Yoel Shoshan, Varda Shalev, Alon Hazan, Vesna Resende Barros, Esma Herzel, Shaked Naor, Adam Spiro, Ayelet Akselrod-Ballin, Michal Rosen-Zvi
Publikováno v:
Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 ISBN: 9783030597245
MICCAI (6)
MICCAI (6)
We investigate the potential contribution of an AI system as a safety net application for radiologists in breast cancer screening. As a safety net, the AI alerts on cases suspected to be malignant which the radiologist did not recommend for a recall.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2d338c152452a63ee7a66de1e2046110
https://doi.org/10.1007/978-3-030-59725-2_22
https://doi.org/10.1007/978-3-030-59725-2_22