Zobrazeno 1 - 10
of 113
pro vyhledávání: '"Kush R. Varshney"'
Autor:
Girmaw Abebe Tadesse, Celia Cintas, Kush R. Varshney, Peter Staar, Chinyere Agunwa, Skyler Speakman, Justin Jia, Elizabeth E. Bailey, Ademide Adelekun, Jules B. Lipoff, Ginikanwa Onyekaba, Jenna C. Lester, Veronica Rotemberg, James Zou, Roxana Daneshjou
Publikováno v:
npj Digital Medicine, Vol 6, Iss 1, Pp 1-10 (2023)
Abstract Images depicting dark skin tones are significantly underrepresented in the educational materials used to teach primary care physicians and dermatologists to recognize skin diseases. This could contribute to disparities in skin disease diagno
Externí odkaz:
https://doaj.org/article/0b3cc841ae2c48ca92f068d15d2a5ec8
Autor:
Sanjoy Dey, Prithwish Chakraborty, Bum Chul Kwon, Amit Dhurandhar, Mohamed Ghalwash, Fernando J. Suarez Saiz, Kenney Ng, Daby Sow, Kush R. Varshney, Pablo Meyer
Publikováno v:
Patterns, Vol 3, Iss 5, Pp 100493- (2022)
Summary: Rapid advances in artificial intelligence (AI) and availability of biological, medical, and healthcare data have enabled the development of a wide variety of models. Significant success has been achieved in a wide range of fields, such as ge
Externí odkaz:
https://doaj.org/article/ea48932b08a941d5a85c583bc912ac83
Autor:
Barbara A. Han, Subhabrata Majumdar, Flavio P. Calmon, Benjamin S. Glicksberg, Raya Horesh, Abhishek Kumar, Adam Perer, Elisa B. von Marschall, Dennis Wei, Aleksandra Mojsilović, Kush R. Varshney
Publikováno v:
Epidemics, Vol 27, Iss , Pp 59-65 (2019)
The recent Zika virus (ZIKV) epidemic in the Americas ranks among the largest outbreaks in modern times. Like other mosquito-borne flaviviruses, ZIKV circulates in sylvatic cycles among primates that can serve as reservoirs of spillover infection to
Externí odkaz:
https://doaj.org/article/c36a9d2dd3a64a5c87d96495c6260860
Publikováno v:
Entropy, Vol 23, Iss 12, p 1571 (2021)
The deployment of machine learning (ML) systems in applications with societal impact has motivated the study of fairness for marginalized groups. Often, the protected attribute is absent from the training dataset for legal reasons. However, datasets
Externí odkaz:
https://doaj.org/article/b75d79d5f2a94e949c2f858a7538ed22
Publikováno v:
Journal of Artificial Intelligence Research. 71:1137-1181
In the current era, people and society have grown increasingly reliant on artificial intelligence (AI) technologies. AI has the potential to drive us towards a future in which all of humanity flourishes. It also comes with substantial risks for oppre
Autor:
Ioana Baldini, Mariana Bernagozzi, Sulbha Aggarwal, Mihaela Bornea, Saksham Chawla, Joppe Geluykens, Dmitriy A. Katz-Rogozhnikov, Pratik Mukherjee, Smruthi Ramesh, Sara Rosenthal, Jagrati Sharma, Kush R. Varshney, Laura B. Kleiman, Pradeep Mangalath, Catherine Del Vecchio Fitz
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 35:15988-15990
Thousands of scientific publications discuss evidence on the efficacy of non-cancer generic drugs being tested for cancer. However, trying to manually identify and extract such evidence is intractable at scale. We introduce a natural language process
Autor:
Tian Gao, Nicholas Mattei, Karthikeyan Shanmugam, Dharmashankar Subramanian, Kush R. Varshney, Debarun Bhattacharjya
Publikováno v:
AAAI
We introduce a novel event-driven continuous time Bayesian network (ECTBN) representation to model situations where a system's state variables could be influenced by occurrences of events of various types. In this way, the model parameters and graphi
Autor:
Casey Dugan, Kush R. Varshney, Aleksandra Mojsilovic, Dakuo Wang, Michael Muller, Yaoli Mao, Ioana Baldini
Publikováno v:
Proceedings of the ACM on Human-Computer Interaction. 3:1-23
In recent years there has been an increasing trend in which data scientists and domain experts work together to tackle complex scientific questions. However, such collaborations often face challenges. In this paper, we aim to decipher this collaborat
Autor:
Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilović, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang
As artificial intelligence and machine learning algorithms become increasingly prevalent in society, multiple stakeholders are calling for these algorithms to provide explanations. At the same time, these stakeholders, whether they be affected citize
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::82f29ad8cfcd6915a9931456dc1d914a
http://arxiv.org/abs/2109.12151
http://arxiv.org/abs/2109.12151
Publikováno v:
Entropy
Entropy, Vol 23, Iss 1571, p 1571 (2021)
Entropy; Volume 23; Issue 12; Pages: 1571
Entropy, Vol 23, Iss 1571, p 1571 (2021)
Entropy; Volume 23; Issue 12; Pages: 1571
The deployment of machine learning (ML) systems in applications with societal impact has motivated the study of fairness for marginalized groups. Often, the protected attribute is absent from the training dataset for legal reasons. However, datasets