Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Yoni Halpern"'
Publikováno v:
Scientific Reports, Vol 7, Iss 1, Pp 1-11 (2017)
Abstract Demand for clinical decision support systems in medicine and self-diagnostic symptom checkers has substantially increased in recent years. Existing platforms rely on knowledge bases manually compiled through a labor-intensive process or auto
Externí odkaz:
https://doaj.org/article/5f64696401c341ff9c0a0acb8861ec01
Autor:
Steven Horng, David A Sontag, Yoni Halpern, Yacine Jernite, Nathan I Shapiro, Larry A Nathanson
Publikováno v:
PLoS ONE, Vol 12, Iss 4, p e0174708 (2017)
OBJECTIVE:To demonstrate the incremental benefit of using free text data in addition to vital sign and demographic data to identify patients with suspected infection in the emergency department. METHODS:This was a retrospective, observational cohort
Externí odkaz:
https://doaj.org/article/8bc94f749fd4432a8e0bf7b27949a1c1
Autor:
Colby S. Redfield, Yoni Halpern, David Sontag, Edward Ullman, Steven Horng, David W. Schoenfeld, Larry A. Nathanson, A. Tlimat
Publikováno v:
J Am Med Inform Assoc
ObjectiveLinking emergency medical services (EMS) electronic patient care reports (ePCRs) to emergency department (ED) records can provide clinicians access to vital information that can alter management. It can also create rich databases for researc
Autor:
Hansa Srinivasan, James Atwood, Alexander D'Amour, Yoni Halpern, D. Sculley, Pallavi Baljekar
Publikováno v:
FAT*
As machine learning becomes increasingly incorporated within high impact decision ecosystems, there is a growing need to understand the long-term behaviors of deployed ML-based decision systems and their potential consequences. Most approaches to und
Autor:
Sanjeev Arora, Yoni Halpern, Yichen Wu, David Sontag, David Mimno, Ankur Moitra, Michael Zhu, Rong Ge
Publikováno v:
Communications of the ACM. 61:85-93
Autor:
Weimin Wang, Roman A. Solovyev, Igor Ivanov, Pavel Ostyakov, Sergey I. Nikolenko, D. Sculley, Yoni Halpern, Pallavi Baljekar, Miha Skalic, James Atwood, Eric Breck
Publikováno v:
The NeurIPS '18 Competition ISBN: 9783030291341
Popular large image classification datasets that are drawn from the web present Eurocentric and Americentric biases that negatively impact the generalizability of models trained on them Shreya Shankar et al. (No classification without representation:
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3f99bb5317ce25a9bb78aaff036005ef
https://doi.org/10.1007/978-3-030-29135-8_6
https://doi.org/10.1007/978-3-030-29135-8_6
Autor:
Shelley Calder, Larry A. Nathanson, David Sontag, Yacine Jernite, Nathaniel R. Greenbaum, Yoni Halpern, Steven Horng
Publikováno v:
International journal of medical informatics. 132
To determine the effect of a domain-specific ontology and machine learning-driven user interfaces on the efficiency and quality of documentation of presenting problems (chief complaints) in the emergency department (ED).As part of a quality improveme
Publikováno v:
Journal of the American Medical Informatics Association : JAMIA
Background Electronic medical records (EMRs) hold a tremendous amount of information about patients that is relevant to determining the optimal approach to patient care. As medicine becomes increasingly precise, a patient’s electronic medical recor
Autor:
Daniel Newburger, D. Sculley, Yaniv Ovadia, Josh Livni, Yoni Halpern, Ryan Poplin, Dilip Krishnan, Tiantian Zha
Publikováno v:
KDD
Mosquito-borne illnesses such as dengue, chikungunya, and Zika are major global health problems, which are not yet addressable with vaccines and must be countered by reducing mosquito populations. The Sterile Insect Technique (SIT) is a promising alt
Publikováno v:
Scientific Reports
Scientific Reports, Vol 7, Iss 1, Pp 1-11 (2017)
Scientific Reports, Vol 7, Iss 1, Pp 1-11 (2017)
Demand for clinical decision support systems in medicine and self-diagnostic symptom checkers has substantially increased in recent years. Existing platforms rely on knowledge bases manually compiled through a labor-intensive process or automatically