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Continuous monitoring of propofol in human serum with fouling compensation by support vector classifier
Publications associées (40)
Using Machine Learning to Predict Mortality for COVID-19 Patients on Day 0 in the ICU
Nahal Mansouri, Sahand Jamal Rahi
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 ...
FRONTIERS MEDIA SA2022Predicting Superagers by Machine Learning Classification Based on the Functional Brain Connectome Using Resting-State Functional Magnetic Resonance Imaging
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 ...
OXFORD UNIV PRESS INC2021Parametrized classifiers for optimal EFT sensitivity
Andrea Wulzer, Alfredo Glioti, Siyu Chen
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 ...
SPRINGER2021Weight Erosion: An Update Aggregation Scheme for Personalized Collaborative Machine Learning
Martin Jaggi, Mary-Anne Hartley, Sai Praneeth Reddy Karimireddy, Felix Hans Michel Grimberg
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, Cham2020The diagnostic potential of multimodal neuroimaging measures in Parkinson's disease and atypical parkinsonism
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 ...
WILEY2020Machine learning based detection of digital documents maliciously recaptured from displays
Touradj Ebrahimi, Evgeniy Upenik, Saleh Gholam Zadeh
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 ...
2020Occupancy detection and tracking in buildings using floor-vibration signals
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 ...
EPFL2020Measuring the effect of nuisance variables on classifiers
Pascal Frossard, Alhussein Fawzi
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 ...
2016Presentation Attack Detection Using Long-Term Spectral Statistics for Trustworthy Speaker Verification
Sébastien Marcel, Hannah Muckenhirn
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 ...
Ieee2016Dictionary learning for fast classification based on soft-thresholding
Pascal Frossard, Alhussein Fawzi
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 ...
Springer2015