artiq-pft

We aim to investigate the representativeness of an AI diagnostic model for pulmonary function testing (ArtiQ.PFT) to its clinical usage.

by Nevena Mikic Sep 20, 2024

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.

by Nevena Mikic Sep 20, 2024

This study shows that AI-based decision support on PFT interpretation improves accurate and early ILD diagnosis.

by Nevena Mikic Dec 26, 2023

This study investigates the speed at which an expert can perform PFT interpretations.

by Nevena Mikic Dec 26, 2023

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).

by Nevena Mikic Dec 26, 2023

This study with 19 pulmonologists and 60 retrospective cases shows an improvement in diagnostic accuracy of the primary diagnosis from 44% to 63%.

by Nevena Mikic Oct 5, 2022

This study where 78 pulmonologists collaborated with ArtiQ.PFT on 24 PFT cases shows an increase in diagnostic accuracy of up to 10%.

by Nevena Mikic Sep 15, 2022

This study where 16 pulmonologists collaborated with ArtiQ.PFT on 24 PFT cases shows an increase in diagnostic accuracy of up to 20%.

by Yuri Van Havere Jun 5, 2022

AI detect respiratory diseases even when PFTs did not include plethysmography data.

by Nevena Mikic Sep 2, 2021

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.

by Yuri Van Havere Sep 24, 2020

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.

by Yuri Van Havere Jun 18, 2019

A study investigating locally interpretable model-agnostic explanation (LIME) to explain the predictions of ArtiQ.PFT's diagnostic probability.

by Yuri Van Havere Mar 8, 2019

The ArtiQ.PFT software perfectly matched the PFT pattern interpretations (100%) and assigned a correct diagnosis in 82% of all 1500 cases.

by Yuri Van Havere Feb 14, 2019