Browsing by Subject "Machine learning"

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Browsing by Subject "Machine learning"

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DeepSPIO: Super Paramagnetic Iron Oxide Particle Quantification using Deep Learning in Magnetic Resonance Imaging

della Maggiora Valdés, Gabriel Eugenio; Milovic Fabregat, Carlos Andrés; Qiu, Wenqi; Liu, Shuang; Milovic Fabregat, Carlos Andres; Sekino, Masaki; Tejos Nunez, Cristian Andres; Uribe Arancibia, Sergio A.; Irarrazaval Barros, Pablo (2020)

The susceptibility of Super Paramagnetic Iron Oxide (SPIO) particles makes them a useful contrast agent for different purposes in MRI. These particles are typically quantified with relaxometry or by measuring the inhomogeneities ...
Galaxy detection and identification using deep learning and data augmentation

González Reyes, Roberto; Munoz, R. P.; Hernandez, C.A. (2018)
Predicting EHL film thickness parameters by machine learning approaches

Marian, Max; Mursak, Jonas; Bartz, Marcel; Profito, Francisco J.; Rosenkranz, Andreas; Wartzack, Sandro (2022)

Non-dimensional similarity groups and analytically solvable proximity equations can be used to estimate integral fluid film parameters of elastohydrodynamically lubricated (EHL) contacts. In this contribution, we demonstrate ...
Respiratory Volume Monitoring: A Machine-Learning Approach to the Non-Invasive Prediction of Tidal Volume and Minute Ventilation

Hurtado Sepúlveda, Daniel; Chávez, J. A. P.; Mansilla, Roberto; Lopez, Roberto; Abusleme Hoffman, Ángel Christian (IEEE, 2020)

Continuous monitoring of ventilatory parameters such as tidal volume (TV) and minute ventilation (MV) has shown to be effective in the prevention of respiratory compromise events in hospitalized patients. However, the ...
Reverse engineering directed gene regulatory networks from transcriptomics and proteomics data of biomining bacterial communities with approximate Bayesian computation and steady-state signalling simulations

Buetti-Dinh, Antoine.; Vera Véliz, Mario Andrés; Herold, Malte.; Christel, Stephan.; El Hajjami, Mohamed.; Delogu, Francesco.; Ilie, Olga.; Bellenberg, Sören.; Wilmes, Paul.; Poetsch, Ansgar. (2020)

Abstract Background Network inference is an important aim of systems biology. It enables the transformation of OMICs datasets into biological knowledge. It consists of ...

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Browsing by Subject "Machine learning"

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