Danilo Cortozi Berton

A Protocol for Validation of Novel AI-Based Framework for Dyspnoea Investigation with CPET

<u>A</u> I- <u>T</u> echniques <u>L</u> oss-Based <u>A</u> lgorithm for <u>S</u> everity Classification (ATLAS): a novel approach for continuous quantification of exertional symptoms during incremental exercise testing

Using AI-techniques to assess dynamic mechanical-ventilatory constraints and exertional dyspnoea during CPET in the CanCOLD study

Novel paradigms for clinical CPET interpretation: dynamic assessment of dyspnoea and ventilation during exercise (DyVe-X)

Mechanical-ventilatory responses and exertional dyspnoea in ever-smokers at risk for COPD in CanCOLD: an AI-based study

Sex- and age-adjusted reference values for dynamic inspiratory constraints during incremental cycle ergometry

Reference values for leg effort during incremental cycle ergometry in non‐trained healthy men and women, aged 19–85

Using AI to expose the mechanisms of exertional dyspnoea in COPD: conflating “excessive” and “constrained” ventilation during incremental CPET

The Effects of Sex and Age on Dynamic Inspiratory Constraints During Incremental Cycle Ergometry

Using AI-Techniques to Develop First Software for Continuous Assessment of Dyspnea and Ventilation During Incremental Cardiopulmonary Exercise Testing (DyVe-X)

Dynamic interactions between submaximal leg effort and dyspnoea during incremental CPET: implications for exercise tolerance in COPD

Quantifying exertional symptoms throughout incremental CPET adds value to peak measurements across the range of COPD severity

Dynamic Ventilatory Reserve During Incremental Exercise: Reference Values and Clinical Validation in Chronic Obstructive Pulmonary Disease

ERS statement on standardisation of cardiopulmonary exercise testing in chronic lung diseases