Publications associées à Optimized Quantification of Multiple Drug Concentrations by WeightedMSE With Machine Learning on Electrochemical Sensor

Publications associées (18)

Application of Deep Learning and Geospatial Analysis in Soil Loss Risk in the Moulouya Watershed, Morocco

Jérôme Chenal, Baraka Jean-Claude Munyaka

This study integrates deep learning and geospatial analysis to enhance soil loss estimation in the Moulouya Watershed, a region prone to erosion due to diverse topography and climatic conditions. Traditional models like the Universal Soil Loss Equation (US ...

AIP Publishing2025

Asynchronous Diffusion Learning with Agent Subsampling and Local Updates

Ali H. Sayed, Elsa Rizk

In this work, we examine a network of agents operating asynchronously, aiming to discover an ideal global model that suits individual local datasets. Our assumption is that each agent independently chooses when to participate throughout the algorithm and t ...

Institute of Electrical and Electronics Engineers Inc.2024

An empirical model to calculate snow depth from daily snow water equivalent: SWE2HS 1.0

Adrien Michel

Many methods exist to model snow densification in order to calculate the depth of a single snow layer or the depth of the total snow cover from its mass. Most of these densification models need to be tightly integrated with an accumulation and melt model a ...

COPERNICUS GESELLSCHAFT MBH2023

Simultaneous and Selective Detection of Etoposide and Methotrexate With Single Electrochemical Sensors for Therapeutic Drug Monitoring

Sandro Carrara, Francesca Rodino

Etoposide (ETO) and methotrexate (MTX) are widely used chemotherapy drugs in cancer treatment, targeting specific cellular processes crucial for DNA replication and cell division. Despite their efficacy, both drugs have significant adverse toxic effects du ...

2023

Uncertainty modeling of household appliance loads for smart energy management

Jean-Louis Scartezzini

Households represent a large share of flexibility on the demand side for assisting the smooth operation of the highly renewable grid. The stochastic nature of activities and various appliance usage patterns of household occupants affects the flexibility po ...

ELSEVIER2021

Wasserstein Distributionally Robust Learning

Soroosh Shafieezadeh Abadeh

Many decision problems in science, engineering, and economics are affected by uncertainty, which is typically modeled by a random variable governed by an unknown probability distribution. For many practical applications, the probability distribution is onl ...

EPFL2020

Context effects on probability estimation

Wei-Hsiang Lin

Many decisions rely on how we evaluate potential outcomes and estimate their corresponding probabilities of occurrence. Outcome evaluation is subjective because it requires consulting internal preferences and is sensitive to context. In contrast, probabili ...

PUBLIC LIBRARY SCIENCE2020

Time-lapse reconstruction of the fracture front from diffracted waves arrivals in laboratory hydraulic fracture experiments

Brice Tanguy Alphonse Lecampion, Dong Liu, Thomas Emmanuel Blum

4-D acoustic imaging via an array of 32 sources/32 receivers is used to monitor hydraulic fracture (HF) propagating in a 250 mm cubic specimen under a true-triaxial state of stress. We present a method based on the arrivals of diffracted waves to reconstru ...

2020

Stochastic Learning Under Random Reshuffling With Constant Step-Sizes

Ali H. Sayed, Stefan Vlaski, Kun Yuan, Bicheng Ying

In empirical risk optimization, it has been observed that stochastic gradient implementations that rely on random reshuffling of the data achieve better performance than implementations that rely on sampling the data uniformly. Recent works have pursued ju ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2019

An Easily Computable Error Estimator In Space And Time For The Wave Equation

Marco Picasso

We propose a cheaper version of a posteriori error estimator from Gorynina et al. (Namer. Anal. (2017)) for the linear second-order wave equation discretized by the Newmark scheme in time and by the finite element method in space. The new estimator preserv ...

EDP Sciences2019

Psychotropic drug-induced genetic-epigenetic modulation of CRTC1 gene is associated with early weight gain in a prospective study of psychiatric patients

Johannes Gräff, Jose Vicente Sanchez Mut

Background: Metabolic side effects induced by psychotropic drugs represent a major health issue in psychiatry. CREB-regulated transcription coactivator 1 (CRTC1) gene plays a major role in the regulation of energy homeostasis and epigenetic mechanisms may ...

2019

A novel electrochemical sensor for non-invasive monitoring of lithium levels in mood disorders

Giovanni De Micheli, Sandro Carrara, Irene Taurino, Francesca Criscuolo

Lithium is the main drug for the treatment of mood disorders. Due to its narrow therapeutic window, Therapeutic Drug Monitoring (TDM) is a norm during therapy in order to avoid adverse effects. Consequently, patients are obliged to frequent check-ups in ho ...

2018

On the Linearity of Bayesian Interpolators for Non-Gaussian Continuous-Time AR(1) Processes

Michaël Unser, Philippe Thévenaz, John Paul Ward, Arash Amini

Bayesian estimation problems involving Gaussian distributions often result in linear estimation techniques. Nevertheless, there are no general statements as to whether the linearity of the Bayesian estimator is restricted to the Gaussian case. The two comm ...

Ieee-Inst Electrical Electronics Engineers Inc2013

Hedging Your Bets by Learning Reward Correlations in the Human Brain

Human subjects are proficient at tracking the mean and variance of rewards and updating these via prediction errors. Here, we addressed whether humans can also learn about higher-order relationships between distinct environmental outcomes, a defining ecolo ...

2011

Frequency comb assisted diode laser spectroscopy for measurement of microcavity dispersion

Tobias Kippenberg

Although invented for precision measurements of single atomic transitions, frequency combs have also become a versatile tool for broadband spectroscopy in recent years. Here, we present a novel and simple approach for broadband spectroscopy, combining the ...

Nature Publishing Group2009

Capturing correlation with subnetworks in route choice models

Michel Bierlaire, Emma Johanna Robert Frejinger

When using random utility models for a route choice problem, a critical issue is the significant correlation among alternatives. There are basically two types of models proposed in the literature to address it: (i) a deterministic correction of the path ut ...

2007

Space-frequency quantization for image compression with directionlets

Martin Vetterli, Vladan Velisavljevic

The standard separable 2-D wavelet transform (WT) has recently achieved a great success in image processing because it provides a sparse representation of smooth images. However, it fails to efficiently capture 1-D discontinuities, like edges or contours. ...

2007

Generalized Smoothing Splines and the Optimal Discretization of the Wiener Filter

Michaël Unser, Thierry Blu

We introduce an extended class of cardinal LL-splines, where L is a pseudo-differential operator satisfying some admissibility conditions. We show that the LL-spline signal interpolation problem is well posed and that its solution is the unique minimizer ...

IEEE2005