2023
DOI: 10.3390/healthcare11111606
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COPD Patients’ Behaviour When Involved in the Choice of Inhaler Device

Abstract: Background: Inhaler therapy plays a crucial role in controlling respiratory symptoms in patients with chronic obstructive pulmonary disease (COPD). Incorrect or partially correct use of inhaler devices causes many chronic obstructive pulmonary disease (COPD) patients to continue to have respiratory symptoms due to poor drug deposition in the airways as a result of poor inhaler technique, leading to increased healthcare costs due to exacerbations and multiple emergency room presentations. Choosing the right inh… Show more

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Cited by 4 publications
(3 citation statements)
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“…COPD is currently one of the most worrying and significant public health problems in many countries. COPD causes an estimated 3.5 million deaths annually and affects over 600 million people worldwide [ 268 ]. The most commonly implemented AI algorithms in the diagnosis, prevention, and classification of COPD disease are decision trees and neural networks [ 269 ].…”
Section: Discussionmentioning
confidence: 99%
“…COPD is currently one of the most worrying and significant public health problems in many countries. COPD causes an estimated 3.5 million deaths annually and affects over 600 million people worldwide [ 268 ]. The most commonly implemented AI algorithms in the diagnosis, prevention, and classification of COPD disease are decision trees and neural networks [ 269 ].…”
Section: Discussionmentioning
confidence: 99%
“…All inhalable formulations have a corresponding inhalation device for administration. In other words, inhalation drug delivery systems are characterized as “drug and device in one”, meaning that inhalation formulations and their inhalation devices are mutually dependent [ 87 , 88 , 89 ]. Similarly, inhalable nano-formulations require a suitable inhalation device, which is de facto the focus of the translation bottleneck.…”
Section: Industrial Translation Of Inhalable Nano-formulations Is Lim...mentioning
confidence: 99%
“…Furthermore, ongoing research endeavors have been dedicated to the development of AI architectures capable of multiclass classification of diverse lung diseases, encompassing pneumonia, lung cancer, tuberculosis (TB), lung opacity, and beyond, thereby exemplifying the expansive scope of AI applications in lung disease categorization [ 36 ]. The landscape of AI-empowered lung disease classification and detection continues to evolve, with concerted efforts directed toward overcoming challenges, enhancing accuracy, and exploring novel techniques such as deep learning, machine learning, and computer vision to augment disease classification capabilities [ 38 ]. Through collaborative interdisciplinary research and technological innovation, the integration of AI into lung disease classification holds immense promise for revolutionizing diagnostic paradigms and improving patient care outcomes in pulmonary medicine.…”
Section: Reviewmentioning
confidence: 99%