Literature DB >> 33618053

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

Alan Kaplan1, Hui Cao2, J Mark FitzGerald3, Nick Iannotti4, Eric Yang4, Janwillem W H Kocks5, Konstantinos Kostikas6, David Price7, Helen K Reddel8, Ioanna Tsiligianni9, Claus F Vogelmeier10, Pascal Pfister11, Paul Mastoridis2.   

Abstract

Artificial intelligence (AI) and machine learning, a subset of AI, are increasingly used 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 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.
Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Artificial intelligence; Asthma; COPD; Diagnosis; Machine learning; Respiratory disease

Mesh:

Year:  2021        PMID: 33618053     DOI: 10.1016/j.jaip.2021.02.014

Source DB:  PubMed          Journal:  J Allergy Clin Immunol Pract


  14 in total

Review 1.  Computational lung modelling in respiratory medicine.

Authors:  Sunder Neelakantan; Yi Xin; Donald P Gaver; Maurizio Cereda; Rahim Rizi; Bradford J Smith; Reza Avazmohammadi
Journal:  J R Soc Interface       Date:  2022-06-08       Impact factor: 4.293

2.  Machine learning in the diagnosis of asthma phenotypes during coronavirus disease 2019 pandemic.

Authors:  Agnieszka Gawlewicz-Mroczka; Adam Pytlewski; Natalia Celejewska-Wójcik; Adam Ćmiel; Anna Gielicz; Marek Sanak; Lucyna Mastalerz
Journal:  Clin Transl Allergy       Date:  2022-10-19       Impact factor: 5.657

Review 3.  Artificial intelligence in arthroplasty.

Authors:  Glen Purnomo; Seng-Jin Yeo; Ming Han Lincoln Liow
Journal:  Arthroplasty       Date:  2021-11-02

4.  Machine learning for detecting COVID-19 from cough sounds: An ensemble-based MCDM method.

Authors:  Nihad Karim Chowdhury; Muhammad Ashad Kabir; Md Muhtadir Rahman; Sheikh Mohammed Shariful Islam
Journal:  Comput Biol Med       Date:  2022-03-17       Impact factor: 6.698

5.  Medical Students' Perceptions towards Digitization and Artificial Intelligence: A Mixed-Methods Study.

Authors:  Adrian Gillissen; Tonja Kochanek; Michaela Zupanic; Jan Ehlers
Journal:  Healthcare (Basel)       Date:  2022-04-13

Review 6.  Where Is the Artificial Intelligence Applied in Dentistry? Systematic Review and Literature Analysis.

Authors:  Andrej Thurzo; Wanda Urbanová; Bohuslav Novák; Ladislav Czako; Tomáš Siebert; Peter Stano; Simona Mareková; Georgia Fountoulaki; Helena Kosnáčová; Ivan Varga
Journal:  Healthcare (Basel)       Date:  2022-07-08

7.  Do Men Have No Need for "Feminist" Artificial Intelligence? Agentic and Gendered Voice Assistants in the Light of Basic Psychological Needs.

Authors:  Laura Moradbakhti; Simon Schreibelmayr; Martina Mara
Journal:  Front Psychol       Date:  2022-06-14

8.  Machine Learning Approaches for Predicting Acute Respiratory Failure, Ventilator Dependence, and Mortality in Chronic Obstructive Pulmonary Disease.

Authors:  Kuang-Ming Liao; Chung-Feng Liu; Chia-Jung Chen; Yu-Ting Shen
Journal:  Diagnostics (Basel)       Date:  2021-12-20

9.  Integration of Artificial Intelligence, Blockchain, and Wearable Technology for Chronic Disease Management: A New Paradigm in Smart Healthcare.

Authors:  Yi Xie; Lin Lu; Fei Gao; Shuang-Jiang He; Hui-Juan Zhao; Ying Fang; Jia-Ming Yang; Ying An; Zhe-Wei Ye; Zhe Dong
Journal:  Curr Med Sci       Date:  2021-12-24

Review 10.  Using Telemedicine to Care for the Asthma Patient.

Authors:  Yudy K Persaud
Journal:  Curr Allergy Asthma Rep       Date:  2022-02-02       Impact factor: 4.919

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.