Continuous monitoring of propofol in human serum with fouling compensation by support vector classifier
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Superagers are defined as older adults who have youthful memory performance comparable to that of middle-aged adults. Classifying superagers based on the brain connectome using machine learning modeling can provide important insights on the physiology unde ...
Rationale: Given the expanding number of COVID-19 cases and the potential for new waves of infection, there is an urgent need for early prediction of the severity of the disease in intensive care unit (ICU) patients to optimize treatment strategies.Objecti ...
Classifiers based on sparse representations have recently been shown to provide excellent results in many visual recognition and classification tasks. However, the high cost of computing sparse representations at test time is a major obstacle that limits t ...
We used to say “seeing is believing": this is no longer true. The digitization is changing all aspects of life and business. One of the more noticeable impacts is in how business documents are being authored, exchanged and processed. Many documents such as ...
Introduction For the diagnosis of Parkinson's disease (PD) and atypical parkinsonism (AP) using neuroimaging, structural measures have been largely employed since structural abnormalities are most noticeable in the diseases. Functional abnormalities have b ...
In sensed buildings, information related to occupant movement helps optimize important functionalities such as security enhancement, energy management, and caregiving. Typical sensing approaches for occupant tracking rely on mobile devices and cameras. The ...
In recent years, there has been a growing interest in developing countermeasures against non zero-effort attacks for speaker verification systems. Until now, the focus has been on logical access attacks, where the spoofed samples are injected into the syst ...
Ieee2016
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We study unbinned multivariate analysis techniques, based on Statistical Learning, for indirect new physics searches at the LHC in the Effective Field Theory framework. We focus in particular on high-energy ZW production with fully leptonic decays, modeled ...
SPRINGER2021
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Background. In medicine and other applications, the copying and sharing of data is impractical for a range of well-considered reasons. With federated learning (FL) techniques, machine learning models can be trained on data spread across several locations w ...
Springer, Cham2020
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In real-world classification problems, nuisance variables can cause wild variability in the data. Nuisance corresponds for example to geometric distortions of the image, occlusions, illumination changes or any other deformations that do not alter the groun ...