Results 41 to 50 of about 473,691 (305)

Privacy-preserving scoring of tree ensembles : a novel framework for AI in healthcare [PDF]

open access: yes, 2018
Machine Learning (ML) techniques now impact a wide variety of domains. Highly regulated industries such as healthcare and finance have stringent compliance and data governance policies around data sharing.
De Cock, Martine   +6 more
core   +1 more source

Quantitative Characterization of the T Cell Receptor Repertoire of Naïve and Memory Subsets Using an Integrated Experimental and Computational Pipeline Which Is Robust, Economical, and Versatile

open access: yesFrontiers in Immunology, 2017
The T cell receptor (TCR) repertoire can provide a personalized biomarker for infectious and non-infectious diseases. We describe a protocol for amplifying, sequencing, and analyzing TCRs which is robust, sensitive, and versatile.
Theres Oakes   +13 more
doaj   +1 more source

24 versus 48 Weeks of Peginterferon Plus Ribavirin in Hepatitis C Virus Genotype 6 Chronically Infected Patients with a Rapid Virological Response: A Non-Inferiority Randomized Controlled Trial. [PDF]

open access: yesPLoS ONE, 2015
The optimal treatment of hepatitis C virus (HCV) genotype 6 is unclear owing to its limited geographic distribution. Because of a high predictive value of rapid virological response (RVR) for sustained virological response (SVR), we conducted an open ...
Qingxian Cai   +21 more
doaj   +1 more source

High-level Counterexamples for Probabilistic Automata [PDF]

open access: yes, 2015
Providing compact and understandable counterexamples for violated system properties is an essential task in model checking. Existing works on counterexamples for probabilistic systems so far computed either a large set of system runs or a subset of the ...
Jansen, Nils   +3 more
core   +1 more source

Vertex labeling and routing in expanded Apollonian networks [PDF]

open access: yes, 2006
We present a family of networks, expanded deterministic Apollonian networks, which are a generalization of the Apollonian networks and are simultaneously scale-free, small-world, and highly clustered. We introduce a labeling of their vertices that allows
Ahuja R   +16 more
core   +3 more sources

POPE: Partial Order Preserving Encoding [PDF]

open access: yes, 2016
Recently there has been much interest in performing search queries over encrypted data to enable functionality while protecting sensitive data. One particularly efficient mechanism for executing such queries is order-preserving encryption/encoding (OPE ...
Apon, Daniel   +3 more
core   +2 more sources

The UPMC OPTIMISE-C19 (OPtimizing Treatment and Impact of Monoclonal antIbodieS through Evaluation for COVID-19) trial: a structured summary of a study protocol for an open-label, pragmatic, comparative effectiveness platform trial with response-adaptive randomization

open access: yesTrials, 2021
Objectives The primary objective is to evaluate the comparative effectiveness of COVID-19 specific monoclonal antibodies (mABs) with US Food and Drug Administration (FDA) Emergency Use Authorization (EUA), alongside UPMC Health System efforts to increase
David T. Huang   +31 more
doaj   +1 more source

Robots Versus Humans: Automated Annotation Accurately Quantifies Essential Ocean Variables of Rocky Intertidal Functional Groups and Habitat State

open access: yesFrontiers in Marine Science, 2021
Standardized methods for effectively and rapidly monitoring changes in the biodiversity of marine ecosystems are critical to assess status and trends in ways that are comparable between locations and over time.
Gonzalo Bravo   +10 more
doaj   +1 more source

Extracting histones for the specific purpose of label-free MS [PDF]

open access: yes, 2016
Extracting histones from cells is the first step in studies that aim to characterize histones and their post-translational modifications (hPTMs) with MS.
De Clerck, Laura   +9 more
core   +2 more sources

Hedging predictions in machine learning [PDF]

open access: yes, 2006
Recent advances in machine learning make it possible to design efficient prediction algorithms for data sets with huge numbers of parameters. This paper describes a new technique for "hedging" the predictions output by many such algorithms, including ...
Gammerman, Alexander, Vovk, Vladimir
core   +4 more sources

Home - About - Disclaimer - Privacy