Zobrazeno 1 - 10
of 465
pro vyhledávání: '"Taylor-Weiner AN"'
Autor:
Gerardin, Ylaine, Shamshoian, John, Shen, Judy, Le, Nhat, Prezioso, Jamie, Abel, John, Finberg, Isaac, Borders, Daniel, Biju, Raymond, Nercessian, Michael, Prasad, Vaed, Lee, Joseph, Wyman, Spencer, Gupta, Sid, Emerson, Abigail, Rahsepar, Bahar, Sanghavi, Darpan, Leung, Ryan, Yu, Limin, Khosla, Archit, Taylor-Weiner, Amaro
Nested pairwise frames is a method for relative benchmarking of cell or tissue digital pathology models against manual pathologist annotations on a set of sampled patches. At a high level, the method compares agreement between a candidate model and p
Externí odkaz:
http://arxiv.org/abs/2306.04709
Autor:
Nguyen, Tan H., Juyal, Dinkar, Li, Jin, Prakash, Aaditya, Nofallah, Shima, Shah, Chintan, Gullapally, Sai Chowdary, Yu, Limin, Griffin, Michael, Sampat, Anand, Abel, John, Lee, Justin, Taylor-Weiner, Amaro
Differences in staining and imaging procedures can cause significant color variations in histopathology images, leading to poor generalization when deploying deep-learning models trained from a different data source. Various color augmentation method
Externí odkaz:
http://arxiv.org/abs/2306.04527
Autor:
Gullapally, Sai Chowdary, Zhang, Yibo, Mittal, Nitin Kumar, Kartik, Deeksha, Srinivasan, Sandhya, Rose, Kevin, Shenker, Daniel, Juyal, Dinkar, Padigela, Harshith, Biju, Raymond, Minden, Victor, Maheshwari, Chirag, Thibault, Marc, Goldstein, Zvi, Novak, Luke, Chandra, Nidhi, Lee, Justin, Prakash, Aaditya, Shah, Chintan, Abel, John, Fahy, Darren, Taylor-Weiner, Amaro, Sampat, Anand
Machine learning algorithms have the potential to improve patient outcomes in digital pathology. However, generalization of these tools is currently limited by sensitivity to variations in tissue preparation, staining procedures and scanning equipmen
Externí odkaz:
http://arxiv.org/abs/2305.02401
SC-MIL: Supervised Contrastive Multiple Instance Learning for Imbalanced Classification in Pathology
Autor:
Juyal, Dinkar, Shingi, Siddhant, Javed, Syed Ashar, Padigela, Harshith, Shah, Chintan, Sampat, Anand, Khosla, Archit, Abel, John, Taylor-Weiner, Amaro
Multiple Instance learning (MIL) models have been extensively used in pathology to predict biomarkers and risk-stratify patients from gigapixel-sized images. Machine learning problems in medical imaging often deal with rare diseases, making it import
Externí odkaz:
http://arxiv.org/abs/2303.13405
Autor:
John Abel, Suyog Jain, Deepta Rajan, Harshith Padigela, Kenneth Leidal, Aaditya Prakash, Jake Conway, Michael Nercessian, Christian Kirkup, Syed Ashar Javed, Raymond Biju, Natalia Harguindeguy, Daniel Shenker, Nicholas Indorf, Darpan Sanghavi, Robert Egger, Benjamin Trotter, Ylaine Gerardin, Jacqueline A. Brosnan-Cashman, Aditya Dhoot, Michael C. Montalto, Chintan Parmar, Ilan Wapinski, Archit Khosla, Michael G. Drage, Limin Yu, Amaro Taylor-Weiner
Publikováno v:
npj Precision Oncology, Vol 8, Iss 1, Pp 1-14 (2024)
Abstract While alterations in nucleus size, shape, and color are ubiquitous in cancer, comprehensive quantification of nuclear morphology across a whole-slide histologic image remains a challenge. Here, we describe the development of a pan-tissue, de
Externí odkaz:
https://doaj.org/article/e77f4d0737534fd0a960be835c387e68
Autor:
Javed, Syed Ashar, Juyal, Dinkar, Padigela, Harshith, Taylor-Weiner, Amaro, Yu, Limin, Prakash, Aaditya
Multiple Instance Learning (MIL) has been widely applied in pathology towards solving critical problems such as automating cancer diagnosis and grading, predicting patient prognosis, and therapy response. Deploying these models in a clinical setting
Externí odkaz:
http://arxiv.org/abs/2206.01794
Autor:
Dacic, Sanja, Travis, William D., Giltnane, Jennifer M., Kos, Filip, Abel, John, Hilz, Stephanie, Fujimoto, Junya, Sholl, Lynette, Ritter, Jon, Khalil, Farah, Liu, Yi, Taylor-Weiner, Amaro, Resnick, Murray, Yu, Hui, Hirsch, Fred R., Bunn, Paul A., Jr., Carbone, David P., Rusch, Valerie, Kwiatkowski, David J., Johnson, Bruce E., Lee, Jay M., Hennek, Stephanie R., Wapinski, Ilan, Nicholas, Alan, Johnson, Ann, Schulze, Katja, Kris, Mark G., Wistuba, Ignacio I.
Publikováno v:
In Journal of Thoracic Oncology May 2024 19(5):719-731
Autor:
Michael Griffin, Sandhya Srinivasan, Jake Conway, Benjamin Glass, Fedaa Najdawi, Ciyue Shen, Shima Nofallah, Chintan Parmar, Michael G Drage, Darpan T Sanghavi, Limin Yu, Raymond Biju, Daniel Borders, Matthew Bronnimann, Laura Chambre, Issac Finberg, Jonathan Glickman, Sidharth Gupta, Natalia Harguindeguy, Nhat Le, Stephanie Hennek, Syed Ashar Javed, Christian Kirkup, Miles Markey, Michael Nercessian, Daniel Shenker, Vignesh Valaboju, Samuel AV Mercedes, Bahar Rahsepar, Ryan Leung, Archit Khosla, Amaro Taylor-Weiner, Ylaine Gerardin, John Abel
Publikováno v:
Journal for ImmunoTherapy of Cancer, Vol 11, Iss Suppl 1 (2023)
Externí odkaz:
https://doaj.org/article/f3f11b9b5b2b4183b35fd446b2be9291
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.