Zobrazeno 1 - 10
of 227
pro vyhledávání: '"Farahani, Hossein"'
Bevacizumab is a widely studied targeted therapeutic drug used in conjunction with standard chemotherapy for the treatment of recurrent ovarian cancer. While its administration has shown to increase the progression-free survival (PFS) in patients wit
Externí odkaz:
http://arxiv.org/abs/2407.20596
Autor:
Mirabadi, Ali Khajegili, Archibald, Graham, Darbandsari, Amirali, Contreras-Sanz, Alberto, Nakhli, Ramin Ebrahim, Asadi, Maryam, Zhang, Allen, Gilks, C. Blake, Black, Peter, Wang, Gang, Farahani, Hossein, Bashashati, Ali
Cancer subtyping is one of the most challenging tasks in digital pathology, where Multiple Instance Learning (MIL) by processing gigapixel whole slide images (WSIs) has been in the spotlight of recent research. However, MIL approaches do not take adv
Externí odkaz:
http://arxiv.org/abs/2402.03592
Autor:
Nakhli, Ramin, Zhang, Allen, Farahani, Hossein, Darbandsari, Amirali, Shenasa, Elahe, Thiessen, Sidney, Milne, Katy, McAlpine, Jessica, Nelson, Brad, Gilks, C Blake, Bashashati, Ali
In clinical practice, many diagnosis tasks rely on the identification of cells in histopathology images. While supervised machine learning techniques require labels, providing manual cell annotations is time-consuming due to the large number of cells
Externí odkaz:
http://arxiv.org/abs/2303.04696
Autor:
Nakhli, Ramin, Moghadam, Puria Azadi, Mi, Haoyang, Farahani, Hossein, Baras, Alexander, Gilks, Blake, Bashashati, Ali
Processing giga-pixel whole slide histopathology images (WSI) is a computationally expensive task. Multiple instance learning (MIL) has become the conventional approach to process WSIs, in which these images are split into smaller patches for further
Externí odkaz:
http://arxiv.org/abs/2303.00865
Autor:
Moghadam, Puria Azadi, Van Dalen, Sanne, Martin, Karina C., Lennerz, Jochen, Yip, Stephen, Farahani, Hossein, Bashashati, Ali
Visual microscopic study of diseased tissue by pathologists has been the cornerstone for cancer diagnosis and prognostication for more than a century. Recently, deep learning methods have made significant advances in the analysis and classification o
Externí odkaz:
http://arxiv.org/abs/2209.13167
Cell identification within the H&E slides is an essential prerequisite that can pave the way towards further pathology analyses including tissue classification, cancer grading, and phenotype prediction. However, performing such a task using deep lear
Externí odkaz:
http://arxiv.org/abs/2208.06445
Autor:
Ahmadvand, Pouya, Farahani, Hossein, Farnell, David, Darbandsari, Amirali, Topham, James, Karasinska, Joanna, Nelson, Jessica, Naso, Julia, Jones, Steven J.M., Renouf, Daniel, Schaeffer, David F., Bashashati, Ali
Publikováno v:
In The American Journal of Pathology December 2024 194(12):2302-2312
Publikováno v:
In Thermal Science and Engineering Progress August 2024 53
Publikováno v:
Computers in Industry, 2021
In this paper, a new approach is proposed for designing transferable soft sensors. Soft sensing is one of the significant applications of data-driven methods in the condition monitoring of plants. While hard sensors can be easily used in various plan
Externí odkaz:
http://arxiv.org/abs/2008.02186