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

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

Subject

Public Health, Environmental and Occupational Health,Pulmonary and Respiratory Medicine,Immunology and Allergy

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

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