Potential role for artificial intelligence/machine learning in the diagnosis of asthma and COPD

Alan Kaplan, Hui Cao, J. Mark FitzGerald, Nick Iannotti, Janwillem W H Kocks, Konstantinos Kostikas, David Price, Helen K. Reddel, Ioanna Tsiligianni, Claus F Vogelmeier, Pascal Pfister, Paul Mastoridis

Research output: Contribution to journalArticlepeer-review


Artificial intelligence (AI) and machine learning, a subset of AI, are increasingly utilized in medicine. AI excels at performing well-defined tasks, such as image recognition; for example, classifying skin biopsy lesions, determining diabetic retinopathy severity, and detecting brain tumors. This article provides an overview of the use of AI in medicine and particularly in respiratory medicine, where it is used to evaluate lung cancer images, diagnose fibrotic lung disease, and more recently is being developed to aid the interpretation of pulmonary function tests and the diagnosis of a range of obstructive and restrictive lung diseases. The development and validation of AI algorithms requires large volumes of well-structured data, and the algorithms must work with variable levels of data quality. It is critical that clinicians review how AI can function in the context of heterogeneous conditions such as asthma and COPD where diagnostic criteria overlap. It will also be important to consider how AI use fits into everyday clinical practice and how issues of patient safety should be addressed. AI has a clear role in providing support for doctors in the clinical workplace but its relatively recent introduction means that confidence in its use still has to be fully established. Overall, AI is expected to play a key role in aiding clinicians in the diagnosis and management of respiratory diseases in the future and it will be exciting to the see benefits that arise for patients and doctors from its use in everyday clinical practice.
Original languageEnglish
JournalThe Journal of Allergy and Clinical Immunology: In Practice
Publication statusAccepted/In press - 15 Feb 2021


  • artificial intelligence
  • machine learning
  • respiratory disease
  • asthma
  • COPD
  • diagnosis

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