Artificial intelligence based software facilitates spirometry quality control in asthma and COPD clinical trials.
Eva TopoleSonia BiondaroIsabella MontagnaSandrine CorreMassimo CorradiSanja StanojevicBrian GrahamNilakash DasKevin RayMarko TopalovicPublished in: ERJ open research (2023)
AI-based software can be used to measure spirometry data quality with comparable accuracy as experts. The assessment is a subjective exercise, with intra- and inter-rater variability even when the criteria are defined very precisely and objectively. By providing consistent results and immediate feedback to the sites, AI may benefit clinical trial conduct and variability reduction.
Keyphrases
- artificial intelligence
- lung function
- clinical trial
- quality control
- big data
- chronic obstructive pulmonary disease
- machine learning
- cystic fibrosis
- air pollution
- deep learning
- physical activity
- data analysis
- phase ii
- high intensity
- open label
- double blind
- study protocol
- phase iii
- electronic health record
- quality improvement
- sleep quality
- depressive symptoms
- body composition