Zobrazeno 1 - 10
of 699
pro vyhledávání: '"P, Farkash"'
Analyzing time-series data that contains personal information, particularly in the medical field, presents serious privacy concerns. Sensitive health data from patients is often used to train machine learning models for diagnostics and ongoing care.
Externí odkaz:
http://arxiv.org/abs/2407.02870
Natural language processing models have experienced a significant upsurge in recent years, with numerous applications being built upon them. Many of these applications require fine-tuning generic base models on customized, proprietary datasets. This
Externí odkaz:
http://arxiv.org/abs/2403.08481
Autor:
Karnan, Haresh, Yang, Elvin, Farkash, Daniel, Warnell, Garrett, Biswas, Joydeep, Stone, Peter
Publikováno v:
Conference on Robot Learning (CoRL 2023)
Terrain awareness, i.e., the ability to identify and distinguish different types of terrain, is a critical ability that robots must have to succeed at autonomous off-road navigation. Current approaches that provide robots with this awareness either r
Externí odkaz:
http://arxiv.org/abs/2309.15302
Autor:
Caitlin M. Blades, Zari P. Dumanian, Yong Wang, Zhaohui Wang, Bing Li, Kia M. Washington, Julia B. Slade, Conor L. Evans, Paula Arrowsmith, Evan A. Farkash, Jason W. Yu, Mark A. Greyson, Christene A. Huang, Nalu Navarro-Alvarez, David W. Mathes
Publikováno v:
Frontiers in Transplantation, Vol 3 (2024)
IntroductionAs research advances in vascularized composite allotransplantation (VCA), large animal models are essential for translational studies related to immune rejection and graft survival. However, procurement of large flaps can cause significan
Externí odkaz:
https://doaj.org/article/7c84b6871fb84c569d2b4b9c9c0cbdc4
Autor:
Ariel Greenberg, Benzion Samueli, Shai Farkash, Yaniv Zohar, Shahar Ish-Shalom, Rami R. Hagege, Dov Hershkovitz
Publikováno v:
Diagnostic Pathology, Vol 19, Iss 1, Pp 1-15 (2024)
Abstract Background Differences in the preparation, staining and scanning of digital pathology slides create significant pre-analytic variability. Algorithm-assisted tools must be able to contend with this variability in order to be applicable in cli
Externí odkaz:
https://doaj.org/article/9de80ebf886c4e5da20392a77bc388de
Autor:
Matthias Diebold, Evan A. Farkash, Jenna Barnes, Heinz Regele, Nicolas Kozakowski, Martina Schatzl, Katharina A. Mayer, Susanne Haindl, Hannes Vietzen, Luis G. Hidalgo, Philip F. Halloran, Farsad Eskandary, Georg A. Böhmig
Publikováno v:
Transplant International, Vol 37 (2024)
Transcript analyses highlight an important contribution of natural killer (NK) cells to microvascular inflammation (MVI) in antibody-mediated rejection (ABMR), but only few immunohistologic studies have quantified their spatial distribution within gr
Externí odkaz:
https://doaj.org/article/4a4b715a60db4143affa7743c8c87e4b
Autor:
Po’okela K. Ng, BS, Dor Yoeli, MD, Joy L. Huang, BA, Yuhuan Luo, MD, Yong Wang, MD, Bing Li, MD, Zhaohui Wang, DVM, Jesse Schold, PhD, Swati Jain, PhD, An-Jey A. Su, PhD, David W. Mathes, MD, Kia M. Washington, MD, Evan Farkash, MD, PhD, Alkesh H. Jani, MD, Christene A. Huang, PhD
Publikováno v:
Transplantation Direct, Vol 10, Iss 6, p e1623 (2024)
Background. Vascularized composite allograft transplantation is a treatment option for complex tissue injuries; however, ischemia reperfusion injury and high acute rejection rates remain a challenge. Hypothermic machine perfusion using acellular stor
Externí odkaz:
https://doaj.org/article/0cb3089453ff4d75963c5a6f190798af
Publikováno v:
Journal of Computing Research and Innovation, Vol 9, Iss 1 (2024)
Most music recommendation systems use data from users' preferences to suggest songs. Popular songs, which have more data, are usually recommended more often, possibly leaving out newer or less popular music. Thus, this study aims to apply machine lea
Externí odkaz:
https://doaj.org/article/f90ca34b9a8e44d8ac045b49fc96cdc1
Autor:
Ariel Farkash, Amit Gordon, Rephael Mohr, Orr Sela, Dmitri Pevni, Tomer Ziv-Baran, Ayelet Grupper, Jonathan E. Kfir, Yanai Ben-Gal
Publikováno v:
PLoS ONE, Vol 19, Iss 2 (2024)
Externí odkaz:
https://doaj.org/article/faf3dd05a49f480da2bcd43cb0002873
Autor:
Aharoni, Ehud, Adir, Allon, Baruch, Moran, Drucker, Nir, Ezov, Gilad, Farkash, Ariel, Greenberg, Lev, Masalha, Ramy, Moshkowich, Guy, Murik, Dov, Shaul, Hayim, Soceanu, Omri
Privacy-preserving solutions enable companies to offload confidential data to third-party services while fulfilling their government regulations. To accomplish this, they leverage various cryptographic techniques such as Homomorphic Encryption (HE),
Externí odkaz:
http://arxiv.org/abs/2011.01805