Espirometry software: development, simulation, theoretical values and final report Source: Eur Respir J 2007; 30: Suppl. 51, 339s Year: 2007
Workstation 2 - Spirometry: performing the test, safety measures, selecting the best values and simulating errors Source: International Congress 2014 – EW7 Spirometry knowledge and basic skills (European spirometry training programme) Year: 2014
Automated volumetric quantification of lung emphysema: comparative analysis of different software products results. Source: Virtual Congress 2020 – Investigations of COPD Year: 2020
NeuroStation – Statistical software based on artificial intelligence and pattern recognition for NSCLC development prediction through comprehensive biomarker analysis Source: Annual Congress 2011 - Quality management for lung cancer patients Year: 2011
Workstation 2 – Spirometry: performing the test, safety measures, selecting the best values and simulating errors Source: International Congress 2014 – EW8 Spirometry knowledge and basic skills (European spirometry training programme) Year: 2014
Workstation 2 – Spirometry: performing the test, safety measures, selecting the best values and simulating errors Source: International Congress 2014 – EW9 Spirometry knowledge and basic skills (European spirometry training programme) Year: 2014
Workstation 3 - Spirometry - how to perform a spirometic test, implementing safety measures, selecting the best values and simulating errors Source: Annual Congress 2013 –Educational skills workshop 7: Spirometry knowledge and basic skills (European spirometry training programme) Year: 2013
Comparison of different analysis algorithms to calculate multiple-breath washout outcomes Source: ERJ Open Res, 4 (3) 00021-2017; 10.1183/23120541.00021-2017 Year: 2018
Limitations of calculating “true” regression slope: impact on estimates of minimal important difference Source: Eur Respir J 2011; 37: 1296-1297 Year: 2011
The annual decline in FEV1 is steeper if it is estimated from baseline data using cross-sectional analysis than obtained by longitudinal analysis Source: Annual Congress 2008 - Air pollution effects on lung and heart Year: 2008
Application of machine learning algorithms to predict loss of asthma control: A post-hoc analysis of INCONTRO study Source: Virtual Congress 2020 – Clinical characteristics and diagnostic tools for phenotyping asthma and COPD Year: 2020
Survival analysis can help determine which TLco prediction equations to use for patient data Source: Annual Congress 2011 - Highlights in lung function 2011 Year: 2011
The best statistical approaches for analysis of GWIS Source: ERS Research Seminar 2015 Year: 2015
Relationships between baseline quantitative CT densitometry and change in outcome measures following lung volume reduction coil (LVRC) treatment Source: Annual Congress 2010 - New toys, old problems: extrapleural lung volume reduction, sedation and comfort in bronchoscopy Year: 2010
Workstation 3 - Spirometry - how to perform a spirometic test, implement safety measures and select the best values Source: Annual Congress 2013 –Educational skills workshop 8: Spirometry knowledge and basic skills (European spirometry training programme) Year: 2013
A statistical model to estimate lung density (LD) utilizing oscillometry (OS), biometrics (BM), patient reported outcomes (PRO) and pulmonary function tests (PFT) Source: International Congress 2016 – The future of lung function is beginning now Year: 2016
A comparative study of the correlations of the COPD assessment test (CAT) scores and high sensitive CRP levels to SPO2 , FEV1 , BODE index, and exacerbation rate Source: Annual Congress 2011 - Treatment strategies, systemic manifestations and biomarkers in airway diseases Year: 2011
Measuring improvement in dyspnoea: should absolute or relative values be used? Source: Eur Respir J 2014; 44: 1700-1703 Year: 2014