In this study, we are investigating the impact of instant feedback provided by an AI algorithm (ArtiQ.QC) on the quality of home spirometry.
by Nevena Mikic Dec 26, 2023
This study explores the value and reliability of artificial intelligence (AI) based quality control software (ArtiQ.QC) to assess spirometry quality in clinical trials using the 2019 ATS/ERS guidelines.
AstraZeneca, a global pharmaceutical leader, has embarked on a transformative journey in clinical trials by integrating digital health solutions.
by Nevena Mikic Aug 30, 2023
Clario integrates AI into clinical trial data collection for spirometry with new partnership with ArtiQ
by Yuri Van Havere Mar 1, 2023
NuvoAir Partners with ArtiQ to Provide AI-Based Over-Reading of Spirometry to Improve Efficiency of Clinical Trials
by Yuri Van Havere Oct 26, 2022
Over-reading spirometry data from the Chinese population to improve data quality in GLI-research.
by Yuri Van Havere Sep 15, 2022
How much do spirometry experts agree with each other… and with themselves?
ArtiQ and patientMpower join forces to provide the best quality home spirometry to patients and healthcare professionals
by Yuri Van Havere May 11, 2022
Spirometry data from preschool children and healthy adults, evaluated by ArtiQ.QC.
by Yuri Van Havere Sep 2, 2021
ArtiQ.QC over-reading & manual over-reading: are the results comparable? And with whom do experts agree more?
Learn more about the consequences of the ATS/ERS 2019 guidelines update.
by Yuri Van Havere May 2, 2021
Find out how AI can improve data quality in epidemiological studies.
by Yuri Van Havere Mar 2, 2021
ArtiQ.QC combines the visual experience of skilled technicians and ATS/ERS quantitative rules in automating the critical phase of spirometry quality control.
by Yuri Van Havere Jun 15, 2020
Neural Networks to standardize spirometric manoeuvre acceptability and usability.
by Yuri Van Havere Jun 3, 2020