Demystification of artificial intelligence for respiratory clinicians managing patients with obstructive lung diseases-Reference-Cited by-同舟云学术

Demystification of artificial intelligence for respiratory clinicians managing patients with obstructive lung diseases

Published:2023-12-02 Issue:12 Volume:17 Page:1207-1219
ISSN:1747-6348
Container-title:Expert Review of Respiratory Medicine
language:en
Short-container-title:Expert Review of Respiratory Medicine

Author:

Antão Joana¹²³⁴,de Mast Jeroen⁵,Marques Alda¹²,Franssen Frits M.E.³⁴,Spruit Martijn A.³⁴,Deng Qichen³⁴

Affiliation:

1. Lab3R – Respiratory Research and Rehabilitation Laboratory, School of Health Sciences, University of Aveiro (ESSUA), Aveiro, Portugal

2. iBiMED – Institute of Biomedicine, Department of Medical Sciences, University of Aveiro, Aveiro, Portugal

3. Department of Research and Development, Ciro, Horn, The Netherlands

4. Department of Respiratory Medicine, Maastricht University Medical Centre, NUTRIM School of Nutrition and Translational Research in Metabolism, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands

5. Economics and Business, University of Amsterdam, Amsterdam, The Netherlands

Funder

AstraZeneca

Boehringer Ingelheim

Chiesi

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/17476348.2024.2302940

Reference74 articles.

1. Artificial intelligence: opportunities and implications for the health workforce

2. Diagnostic Image Analysis Group. AI for radiology: an implementation guide. Available from: https://grand-challenge.org/aiforradiology/?subspeciality=Chest&modality=All&search

3. Global Initiative for Chronic Obstructive Lung Disease (GOLD). GOLD report - global strategy for the diagnosis management and prevention of COPD. 2022. 2022.

4. COPD phenotypes and machine learning cluster analysis: A systematic review and future research agenda

5. A Systematic Review of Asthma Phenotypes Derived by Data-Driven Methods