Concept

Clinical data acquisition

Related publications (33)

Deep learning diagnostic and severity-stratification for interstitial lung diseases and chronic obstructive pulmonary disease in digital lung auscultations and ultrasonography: clinical protocol for an observational case-control study

BackgroundInterstitial lung diseases (ILD), such as idiopathic pulmonary fibrosis (IPF) and non-specific interstitial pneumonia (NSIP), and chronic obstructive pulmonary disease (COPD) are severe, progressive pulmonary disorders with a poor prognosis. Prom ...

BMC2023

PDE-Aware Deep Learning for Inverse Problems in Cardiac Electrophysiology

Alfio Quarteroni, Simone Deparis, Riccardo Tenderini, Stefano Pagani

In this work, we present a PDE-aware deep learning model for the numerical solution to the inverse problem of electrocardiography. The model both leverages data availability and exploits the knowledge of a physically based mathematical model, expressed by ...

2022

Data integration for the numerical simulation of cardiac electrophysiology

Alfio Quarteroni, Andrea Manzoni, Luca Dede', Stefano Pagani

The increasing availability of extensive and accurate clinical data is rapidly shaping cardiovascular care by improving the understanding of physiological and pathological mechanisms of the cardiovascular system and opening new frontiers in designing thera ...

WILEY2021

Wastewater-based estimation of the effective reproductive number of SARS-CoV-2

Tamar Kohn, Krista Rule Wigginton, Xavier Fernandez Cassi, Timothy R. Julian

Background The effective reproductive number, Re, is a critical indicator to monitor disease dynamics, inform regional and national policies, and estimate the effectiveness of interventions. It describes the average number of new infections caused by a sin ...

2021

Wastewater monitoring outperforms case numbers as a tool to track COVID-19 incidence dynamics when test positivity rates are high

Tamar Kohn, Xavier Fernandez Cassi, Joseph Chadi Benoit Lemaitre, Federica Cariti, Alex Tunas Corzon, Timothy R. Julian, Carola Bänziger

Wastewater-based epidemiology (WBE) has been shown to coincide with, or anticipate, confirmed COVID-19 case numbers. During periods with high test positivity rates, however, case numbers may be underreported, whereas wastewater does not suffer from this li ...

2021

Identifying and Characterizing Trans Women in the Swiss HIV Cohort Study as an Epidemiologically Distinct Risk Group

Jacques Fellay

Background As trans women are disproportionately affected by the HIV epidemic, and are still understudied, we aimed to identify and characterize the trans women in the Swiss HIV Cohort Study (SHCS). Methods A combination of criteria from pre-existing cohor ...

OXFORD UNIV PRESS INC2021

Clinical relevance of low-densityPlasmodium falciparumparasitemia in untreated febrile children: A cohort study

Mary-Anne Hartley

Background Low-density (LD)Plasmodiuminfections are missed by standard malaria rapid diagnostic tests (standard mRDT) when the blood antigen concentration is below the detection threshold. The clinical impact of these LD infections is unknown. This study i ...

2020

Wearable multi-electrode platform for ion sensing

Francesca Criscuolo

With the growth of personalized medicine and e-Health, there has been an increasing interest in the development of accurate sensing systems able to support this healthcare revolution for both in- and off-hospital monitoring. Remote biosensing devices can d ...

EPFL2020

Dynamic time domain near-infrared optical tomography based on a SPAD camera

Edoardo Charbon, Scott Anthony Lindner, Martin Wolf, Jingjing Jiang

In many clinical applications it is relevant to observe dynamic changes in oxygenation. Therefore the ability of dynamic imaging with time domain (TD) near-infrared optical tomography (NIROT) will be important. But fast imaging is a challenge. The data acq ...

2020

The detection of two-component mixture alternatives

Daria Rukina

In this thesis, we deal with one of the facets of the statistical detection problem. We study a particular type of alternative, the mixture model. We consider testing where the null hypothesis corresponds to the absence of a signal, represented by some kno ...

EPFL2018

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