Zobrazeno 1 - 10
of 94
pro vyhledávání: '"Sow, Daby"'
For highly regulated industries such as banking and healthcare, one of the major hindrances to the adoption of cloud computing is compliance with regulatory standards. This is a complex problem due to many regulatory and technical specification (tech
Externí odkaz:
http://arxiv.org/abs/2206.11187
Organizations struggle to handle sheer number of vulnerabilities in their cloud environments. The de facto methodology used for prioritizing vulnerabilities is to use Common Vulnerability Scoring System (CVSS). However, CVSS has inherent limitations
Externí odkaz:
http://arxiv.org/abs/2206.11182
Autor:
Adam, Constantin, Bulut, Muhammed Fatih, Sow, Daby, Ocepek, Steven, Bedell, Chris, Ngweta, Lilian
Modern organizations struggle with insurmountable number of vulnerabilities that are discovered and reported by their network and application vulnerability scanners. Therefore, prioritization and focus become critical, to spend their limited time on
Externí odkaz:
http://arxiv.org/abs/2206.11171
Autor:
Chakraborty, Prithwish, Codella, James, Madan, Piyush, Li, Ying, Huang, Hu, Park, Yoonyoung, Yan, Chao, Zhang, Ziqi, Gao, Cheng, Nyemba, Steve, Min, Xu, Basak, Sanjib, Ghalwash, Mohamed, Shahn, Zach, Suryanarayanan, Parthasararathy, Buleje, Italo, Harrer, Shannon, Miller, Sarah, Rajmane, Amol, Walsh, Colin, Wanderer, Jonathan, Reed, Gigi Yuen, Ng, Kenney, Sow, Daby, Malin, Bradley A.
Deep learning architectures have an extremely high-capacity for modeling complex data in a wide variety of domains. However, these architectures have been limited in their ability to support complex prediction problems using insurance claims data, su
Externí odkaz:
http://arxiv.org/abs/2104.04377
A pervasive design issue of AI systems is their explainability--how to provide appropriate information to help users understand the AI. The technical field of explainable AI (XAI) has produced a rich toolbox of techniques. Designers are now tasked wi
Externí odkaz:
http://arxiv.org/abs/2104.03483
Despite the large number of patients in Electronic Health Records (EHRs), the subset of usable data for modeling outcomes of specific phenotypes are often imbalanced and of modest size. This can be attributed to the uneven coverage of medical concept
Externí odkaz:
http://arxiv.org/abs/2009.02188
Autor:
Suryanarayanan, Parthasarathy, Iyer, Bhavani, Chakraborty, Prithwish, Hao, Bibo, Buleje, Italo, Madan, Piyush, Codella, James, Foncubierta, Antonio, Pathak, Divya, Miller, Sarah, Rajmane, Amol, Harrer, Shannon, Yuan-Reed, Gigi, Sow, Daby
Many institutions within the healthcare ecosystem are making significant investments in AI technologies to optimize their business operations at lower cost with improved patient outcomes. Despite the hype with AI, the full realization of this potenti
Externí odkaz:
http://arxiv.org/abs/2007.12780
Increased availability of electronic health records (EHR) has enabled researchers to study various medical questions. Cohort selection for the hypothesis under investigation is one of the main consideration for EHR analysis. For uncommon diseases, co
Externí odkaz:
http://arxiv.org/abs/2005.06434
The potential of Reinforcement Learning (RL) has been demonstrated through successful applications to games such as Go and Atari. However, while it is straightforward to evaluate the performance of an RL algorithm in a game setting by simply using it
Externí odkaz:
http://arxiv.org/abs/2005.04301
Autor:
Li, Rui, Shahn, Zach, Li, Jun, Lu, Mingyu, Chakraborty, Prithwish, Sow, Daby, Ghalwash, Mohamed, Lehman, Li-wei H.
Counterfactual prediction is a fundamental task in decision-making. G-computation is a method for estimating expected counterfactual outcomes under dynamic time-varying treatment strategies. Existing G-computation implementations have mostly employed
Externí odkaz:
http://arxiv.org/abs/2003.10551