artiq-qc
This analysis aims to evaluate the adherence to the study protocol and the spirometry quality when performing unsupervised home spirometry.
This study introduces an AI model to automatically classify the quality of PEF curves.
This analysis aimed to determine whether the quality of a patient's onsite spirometry could predict the quality of their home spirometry.
Accurate FVC measurements are essential for correct interpretation of spirometry. The updated ATS/ERS-technical standards for spirometry require at least one of three EOFE criteria to be met.
We are happy to announce our partnership with AstraZeneca, reflecting our shared dedication to advancing research on respiratory conditions and enhancing the quality of life for individuals with lung diseases.
In this study, we are investigating the impact of instant feedback provided by an AI algorithm (ArtiQ.QC) on the quality of home spirometry.
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.
Clario integrates AI into clinical trial data collection for spirometry with new partnership with ArtiQ
NuvoAir Partners with ArtiQ to Provide AI-Based Over-Reading of Spirometry to Improve Efficiency of Clinical Trials
Over-reading spirometry data from the Chinese population to improve data quality in GLI-research.
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
Spirometry data from preschool children and healthy adults, evaluated by ArtiQ.QC.
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.
ArtiQ.QC over-reading & manual over-reading: are the results comparable? And with whom do experts agree more?
Find out how AI can improve data quality in epidemiological studies.
ArtiQ.QC combines the visual experience of skilled technicians and ATS/ERS quantitative rules in automating the critical phase of spirometry quality control.
Neural Networks to standardize spirometric manoeuvre acceptability and usability.