artiq-pft
We aim to investigate the representativeness of an AI diagnostic model for pulmonary function testing (ArtiQ.PFT) to its clinical usage.
ILD is a rare progressive disease with a huge burden. We aim to utilize AI model for pulmonary function testing (ArtiQ.PFT) to leverage ILD related data insights.
This study shows that AI-based decision support on PFT interpretation improves accurate and early ILD diagnosis.
This study investigates the speed at which an expert can perform PFT interpretations.
This study investigates how the recently published ERS/ATS guidelines for lung function interpretation (Stanojevic 2021) affect patient classification compared to the previous document (Pellegrino 2005).
This study with 19 pulmonologists and 60 retrospective cases shows an improvement in diagnostic accuracy of the primary diagnosis from 44% to 63%.
This study where 78 pulmonologists collaborated with ArtiQ.PFT on 24 PFT cases shows an increase in diagnostic accuracy of up to 10%.
This study where 16 pulmonologists collaborated with ArtiQ.PFT on 24 PFT cases shows an increase in diagnostic accuracy of up to 20%.
AI detect respiratory diseases even when PFTs did not include plethysmography data.
Watch the presentation below to get an overview of the latest applications of AI in respiratory medicine and to learn how doctors and AI can work together as a complimentary team.
ArtiQ, a KU Leuven spin-off company which helps doctors diagnose, treat and monitor respiratory problems, announces that it has successfully concluded its seed financing round, raising € 1 million euro. The financing will be used to launch ArtiQ|PFT, a decision support tool that offers pulmonologists a fast, reliable and standardized evaluation of a patient’s lung function.
A study investigating locally interpretable model-agnostic explanation (LIME) to explain the predictions of ArtiQ.PFT's diagnostic probability.
The ArtiQ.PFT software perfectly matched the PFT pattern interpretations (100%) and assigned a correct diagnosis in 82% of all 1500 cases.