Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Michaela Hardt"'
Autor:
Alvin Rajkomar, Eyal Oren, Kai Chen, Andrew M. Dai, Nissan Hajaj, Michaela Hardt, Peter J. Liu, Xiaobing Liu, Jake Marcus, Mimi Sun, Patrik Sundberg, Hector Yee, Kun Zhang, Yi Zhang, Gerardo Flores, Gavin E. Duggan, Jamie Irvine, Quoc Le, Kurt Litsch, Alexander Mossin, Justin Tansuwan, De Wang, James Wexler, Jimbo Wilson, Dana Ludwig, Samuel L. Volchenboum, Katherine Chou, Michael Pearson, Srinivasan Madabushi, Nigam H. Shah, Atul J. Butte, Michael D. Howell, Claire Cui, Greg S. Corrado, Jeffrey Dean
Publikováno v:
npj Digital Medicine, Vol 1, Iss 1, Pp 1-10 (2018)
Artificial intelligence: Algorithm predicts clinical outcomes for hospital inpatients Artificial intelligence outperforms traditional statistical models at predicting a range of clinical outcomes from a patient’s entire raw electronic health record
Externí odkaz:
https://doaj.org/article/a9b3a7cdda6e486cba268a16dc6760b2
Autor:
Michele Donini, Jason Gelman, Ankit Siva, Satish Gollaprolu, Michaela Hardt, Scott Rees, Keerthan Vasist, ErhYuan Tsai, Kevin Haas, Nick McCarthy, Xinyu Liu, Tyler Hill, Xiaoguang Chen, John He, Sanjiv Ranjan Das, Xiaoyi Cheng, Muhammad Bilal Zafar, Pedro Larroy, Ashish Rathi, Krishnaram Kenthapadi, Pinar Yilmaz
Understanding the predictions made by machine learning (ML) models and their potential biases remains a challenging and labor-intensive task that depends on the application, the dataset, and the specific model. We present Amazon SageMaker Clarify, an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1728d15bde7bafc389e8a182ecf5eb82
Autor:
Marshall H. Chin, Michaela Hardt
Publikováno v:
Am J Bioeth
Increasingly, data scientists are training machine-learning (ML) models for diagnosis, treatment selection, and resource allocation. The U.S. Food and Drug Administration has given regulatory appro...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8cd0ffba5dd1e0036cf4a53faca436ec
https://europepmc.org/articles/PMC8647714/
https://europepmc.org/articles/PMC8647714/
Autor:
Claire Cui, Alvin Rajkomar, Andrew M. Dai, Greg S. Corrado, Michaela Hardt, Gerardo Flores, Moritz Hardt, Michael D. Howell
Publikováno v:
CHIL
Much work aims to explain a model's prediction on a static input. We consider explanations in a temporal setting where a stateful dynamical model produces a sequence of risk estimates given an input at each time step. When the estimated risk increase
Autor:
Jake Marcus, Kurt Litsch, Claire Cui, Srinivasan Madabushi, Nigam H. Shah, Gavin E. Duggan, Samuel L. Volchenboum, Alexander Mossin, Greg S. Corrado, Michael Pearson, Yi Zhang, Kai Chen, Eyal Oren, Michael D. Howell, Jamie Irvine, Justin Tansuwan, Jeffrey Dean, Quoc V. Le, Andrew M. Dai, Xiaobing Liu, De Wang, Alvin Rajkomar, Peter J. Liu, Mimi Sun, Jimbo Wilson, Katherine Chou, Patrik Sundberg, Nissan Hajaj, Hector Yee, James Wexler, Dana Ludwig, Kun Zhang, Gerardo Flores, Atul J. Butte, Michaela Hardt
Publikováno v:
NPJ Digital Medicine
NPJ digital medicine, vol 1, iss 1
npj Digital Medicine, Vol 1, Iss 1, Pp 1-10 (2018)
NPJ digital medicine, vol 1, iss 1
npj Digital Medicine, Vol 1, Iss 1, Pp 1-10 (2018)
Predictive modeling with electronic health record (EHR) data is anticipated to drive personalized medicine and improve healthcare quality. Constructing predictive statistical models typically requires extraction of curated predictor variables from no
Autor:
Kai Chen, Andrew M. Dai, Kathryn Rough, Jeffrey Dean, Alvin Rajkomar, Michaela Hardt, Mimi Sun
Publikováno v:
npj Digital Medicine, Vol 1, Iss 1, Pp 1-2 (2018)
NPJ Digital Medicine
NPJ Digital Medicine
Publikováno v:
Annals of Internal Medicine. 169:866
Machine learning is used increasingly in clinical care to improve diagnosis, treatment selection, and health system efficiency. Because machine-learning models learn from historically collected data, populations that have experienced human and struct
Autor:
Suman Nath, Michaela Hardt
Publikováno v:
ACM Conference on Computer and Communications Security
Mobile advertising is an increasingly important driver in the Internet economy. We point out fundamental trade-offs between important variables in the mobile advertisement ecosystem. In order to increase relevance, ad campaigns tend to become more ta
Publikováno v:
ACM Conference on Computer and Communications Security
Today, websites commonly use third party web analytics services t obtain aggregate information about users that visit their sites. This information includes demographics and visits to other sites as well as user behavior within their own sites. Unfor