AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Dry Powder Inhalers

Showing 1 to 4 of 4 articles

Clear Filters

Development of an Inline Dry Powder Inhaler That Requires Low Air Volume.

Journal of aerosol medicine and pulmonary drug delivery
BACKGROUND: Inline dry powder inhalers (DPIs) are actuated by an external air source and have distinct advantages for delivering aerosols to infants and children, and to individuals with compromised lung function or who require ventilator support. Ho...

Predictive machine learning algorithm for COPD exacerbations using a digital inhaler with integrated sensors.

BMJ open respiratory research
PURPOSE: By using data obtained with digital inhalers, machine learning models have the potential to detect early signs of deterioration and predict impending exacerbations of chronic obstructive pulmonary disease (COPD) for individual patients. This...

Predicting the Fine Particle Fraction of Dry Powder Inhalers Using Artificial Neural Networks.

Journal of pharmaceutical sciences
Dry powder inhalers are increasingly popular for delivering drugs to the lungs for the treatment of respiratory diseases, but are complex products with multivariate performance determinants. Heuristic product development guided by in vitro aerosol pe...

In vitro and in vivo performance modelling and optimisation of different dry powder inhalers: A complementary study of neural networks, genetic algorithms and decision trees.

International journal of clinical practice
INTRODUCTION: Aerosol delivery from DPIs could be affected by different factors. This study aimed to evaluate and predict the effects of different factors on drug delivery from DPIs.