Artificial Intelligence/Machine Learning in Respiratory Medicine and Potential Role in Asthma and COPD Diagnosis

被引：107

作者：

Kaplan, Alan ^{[1
]}

Cao, Hui ^{[2
]}

FitzGerald, J. Mark ^{[3
]}

Iannotti, Nick ^{[4
]}

Yang, Eric ^{[4
]}

Kocks, Janwillem W. H. ^{[5
,6
,7
]}

Kostikas, Konstantinos ^{[8
]}

Price, David ^{[7
,9
]}

Reddel, Helen K. ^{[10
]}

Tsiligianni, Ioanna ^{[11
]}

Vogelmeier, Claus F. ^{[12
,13
]}

Pfister, Pascal ^{[14
]}

Mastoridis, Paul ^{[2
]}

机构：

[1] Univ Toronto, Family Phys Airways Grp Canada, Toronto, ON, Canada

[2] Novartis Pharmaceut, E Hanover, NJ USA

[3] Univ British Columbia, Dept Med, Div Resp Med, Vancouver, BC, Canada

[4] Novartis Inst Biomed Res, Cambridge, MA USA

[5] Gen Practitioners Res Inst, Groningen, Netherlands

[6] Univ Groningen, Univ Med Ctr Groningen, GRIAC Res Inst, Groningen, Netherlands

[7] Observat & Pragmat Res Inst, Singapore, Singapore

[8] Univ Ioannina, Resp Med Dept, Sch Med, Ioannina, Greece

[9] Univ Aberdeen, Div Appl Hlth Sci, Ctr Acad Primary Care, Aberdeen, Scotland

[10] Univ Sydney, Woolcock Inst Med Res, Sydney, NSW, Australia

[11] Univ Crete, Fac Med, Dept Social Med, Iraklion, Greece

[12] Philipps Univ Marburg, Univ Med Ctr Giessen & Marburg, Dept Med Pulm & Crit Care Med, Marburg, Germany

[13] German Ctr Lung Res DZL, Marburg, Germany

[14] Novartis Pharma AG, Basel, Switzerland

来源：

JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY-IN PRACTICE | 2021年 / 9卷 / 06期

关键词：

Asthma; Artificial intelligence; COPD; Diagnosis; Machine learning; Respiratory disease; INHALED CORTICOSTEROIDS; NEURAL-NETWORKS; PRIMARY-CARE; CLASSIFICATION; MISDIAGNOSIS; TUBERCULOSIS; PREVENTION; ADULTS;

D O I：

10.1016/j.jaip.2021.02.014

中图分类号：

R392 [医学免疫学];

学科分类号：

100102 ;

摘要：

Artificial intelligence (AI) and machine learning, a subset of AI, are increasingly used in medicine. AI excels at performing welldefined 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 important that clinicians understand how AI can function in the context of heterogeneous conditions such as asthma and chronic obstructive pulmonary disease where diagnostic criteria overlap, 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 see the benefits that arise for patients and doctors from its use in everyday clinical practice. (C) 2021 The Authors. Published by Elsevier Inc. on behalf of the American Academy of Allergy, Asthma & Immunology.

引用

页码：2255 / 2261

页数：7

共 62 条

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