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Marko Topalovic

Showing results (11-20 of 25) with videos related to

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The European Respiratory Journal|June 13, 2020
Deep-learning algorithm helps to standardise ATS/ERS spirometric acceptability and usability criteriaNilakash Das, Kenneth Verstraete, Sanja Stanojevic, et al.
Respiratory Research|July 22, 2015
Airways resistance and specific conductance for the diagnosis of obstructive airways diseasesMarko Topalovic, Eric Derom, Christian R Osadnik, et al.
Thorax|April 3, 2023
Estimating individual treatment effects on COPD exacerbations by causal machine learning on randomised controlled trialsKenneth Verstraete, Iwein Gyselinck, Helene Huts, et al.
ERJ Open Research|February 13, 2023
Artificial intelligence based software facilitates spirometry quality control in asthma and COPD clinical trialsEva Topole, Sonia Biondaro, Isabella Montagna, et al.
Respiratory Research|November 21, 2013
Computer quantification of airway collapse on forced expiration to predict the presence of emphysemaMarko Topalovic, Vasileios Exadaktylos, Anneleen Peeters, et al.
Journal of Applied Physiology (Bethesda, Md. : 1985)|March 16, 2018
Inspiratory muscle training reduces diaphragm activation and dyspnea during exercise in COPDDaniel Langer, Casey Ciavaglia, Azmy Faisal, et al.
ERJ Open Research|September 20, 2023
Machine learning to differentiate pulmonary hypertension due to left heart disease from pulmonary arterial hypertensionKatleen Swinnen, Kenneth Verstraete, Claudia Baratto, et al.
Brazilian Journal of Physical Therapy|August 6, 2018
Mechanical properties, safety and resistance values of Lemgruber<sup>®</sup> elastic tubingFabiano Francisco de Lima, Carlos Augusto Camillo, Elton Aparecido Prado Dos Reis, et al.
Respiratory Research|January 19, 2023
Principal component analysis of flow-volume curves in COPDGene to link spirometry with phenotypes of COPDKenneth Verstraete, Nilakash Das, Iwein Gyselinck, et al.
The European Respiratory Journal|February 16, 2019
Artificial intelligence outperforms pulmonologists in the interpretation of pulmonary function testsMarko Topalovic, Nilakash Das, Pierre-Régis Burgel, et al.
Pageof 3

Showing results (11-20 of 25) with videos related to

Sort By:
Pageof 3
The European Respiratory Journal|June 13, 2020
Deep-learning algorithm helps to standardise ATS/ERS spirometric acceptability and usability criteriaNilakash Das, Kenneth Verstraete, Sanja Stanojevic, et al.
Respiratory Research|July 22, 2015
Airways resistance and specific conductance for the diagnosis of obstructive airways diseasesMarko Topalovic, Eric Derom, Christian R Osadnik, et al.
Thorax|April 3, 2023
Estimating individual treatment effects on COPD exacerbations by causal machine learning on randomised controlled trialsKenneth Verstraete, Iwein Gyselinck, Helene Huts, et al.
ERJ Open Research|February 13, 2023
Artificial intelligence based software facilitates spirometry quality control in asthma and COPD clinical trialsEva Topole, Sonia Biondaro, Isabella Montagna, et al.
Respiratory Research|November 21, 2013
Computer quantification of airway collapse on forced expiration to predict the presence of emphysemaMarko Topalovic, Vasileios Exadaktylos, Anneleen Peeters, et al.
Journal of Applied Physiology (Bethesda, Md. : 1985)|March 16, 2018
Inspiratory muscle training reduces diaphragm activation and dyspnea during exercise in COPDDaniel Langer, Casey Ciavaglia, Azmy Faisal, et al.
ERJ Open Research|September 20, 2023
Machine learning to differentiate pulmonary hypertension due to left heart disease from pulmonary arterial hypertensionKatleen Swinnen, Kenneth Verstraete, Claudia Baratto, et al.
Brazilian Journal of Physical Therapy|August 6, 2018
Mechanical properties, safety and resistance values of Lemgruber<sup>®</sup> elastic tubingFabiano Francisco de Lima, Carlos Augusto Camillo, Elton Aparecido Prado Dos Reis, et al.
Respiratory Research|January 19, 2023
Principal component analysis of flow-volume curves in COPDGene to link spirometry with phenotypes of COPDKenneth Verstraete, Nilakash Das, Iwein Gyselinck, et al.
The European Respiratory Journal|February 16, 2019
Artificial intelligence outperforms pulmonologists in the interpretation of pulmonary function testsMarko Topalovic, Nilakash Das, Pierre-Régis Burgel, et al.
Pageof 3