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

Kaplan, Alan; Cao, Hui; FitzGerald, J. Mark; Iannotti, Nick; Yang, Eric; Kocks, Janwillem; Κostikas, Κonstantinos; Price, David; Reddel, Helen; Tsiligianni, Ioanna; Vogelmeier, Claus; Pfister, Pascal; Mastoridis, Paul

doi:10.1016/j.jaip.2021.02.014

Cited by 106 publications

(71 citation statements)

References 58 publications

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“…Chronic pulmonary diseases mainly include chronic bronchitis, pulmonary tuberculosis, chronic obstructive pulmonary disease (COPD), and interstitial pulmonary disease [33][34][35] . Common respiratory disorder diseases have a significant morbidity and mortality, and approximately 210 million people are affected around the world; therefore, chronic pulmonary diseases have become a serious health problem for the elderly [33] . For these patients, continuous monitoring of their disease progression and physical health status is essential for controlling their disease.…”

Section: Pulmonary Diseasesmentioning

confidence: 99%

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

Xie

Gao

et al. 2021

CURR MED SCI

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Chronic diseases are a growing concern worldwide, with nearly 25% of adults suffering from one or more chronic health conditions, thus placing a heavy burden on individuals, families, and healthcare systems. With the advent of the “Smart Healthcare” era, a series of cutting-edge technologies has brought new experiences to the management of chronic diseases. Among them, smart wearable technology not only helps people pursue a healthier lifestyle but also provides a continuous flow of healthcare data for disease diagnosis and treatment by actively recording physiological parameters and tracking the metabolic state. However, how to organize and analyze the data to achieve the ultimate goal of improving chronic disease management, in terms of quality of life, patient outcomes, and privacy protection, is an urgent issue that needs to be addressed. Artificial intelligence (AI) can provide intelligent suggestions by analyzing a patient’s physiological data from wearable devices for the diagnosis and treatment of diseases. In addition, blockchain can improve healthcare services by authorizing decentralized data sharing, protecting the privacy of users, providing data empowerment, and ensuring the reliability of data management. Integrating AI, blockchain, and wearable technology could optimize the existing chronic disease management models, with a shift from a hospital-centered model to a patient-centered one. In this paper, we conceptually demonstrate a patient-centric technical framework based on AI, blockchain, and wearable technology and further explore the application of these integrated technologies in chronic disease management. Finally, the shortcomings of this new paradigm and future research directions are also discussed.

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Section: Pulmonary Diseasesmentioning

confidence: 99%

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

Xie

Gao

et al. 2021

CURR MED SCI

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“…Precisely, computer programmer are currently using machine learning to develop automatic classifiers information from different networks which produce signals that are going to be used for performing certain tasks. They will be used as pattern recognition to optimize and detect airflow obstruction in patients [119][120][121][122]. Ultimately, individualized CFD studies may be a viable diagnostic tool in the nearest future with the integration of deep learning to derive patient's specific data.…”

Section: Prospectsmentioning

confidence: 99%

Computational Fluid Dynamics Modeling in Respiratory Airways Obstruction: <i>Current Applications and Prospects</i>

Ayodele¹,

Oluwatosin²,

Taiwo³

et al. 2021

IJBSE

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Breathing conditions pertaining to nasal obstruction, obstructive sleep apnea, and airflow resistance in the human lower airways have been investigated extensively by researchers over the years. Due to the availability of advanced computer numerical models, such as computational fluid dynamics (CFD), researchers have made progressive studies of airflow characteristic, especially the effects of airflow pressure, velocity and wall shear stress in human obstructive airways. Studies utilizing CFD have enhanced clinical understanding of the physiology and pathophysiology of the respiratory system through the concept of three-dimensional models that facilitate airflow simulation. The main objective of this article is to review recent CFD literature on nasal airflow and lower airway obstruction. The review covers the role of segmentation threshold in the outcome of airflow simulation in the nasal cavity, and results of fluid structure interaction (FSI) and computational fluid dynamics in nasal obstruction and airway collapse in obstructive sleep apnea were also correlated. For models of the lower airways, we evaluated the effect of extra-thoracic airway (ETA) on downstream airflow during simulation against the popular Weibel's model. In the concluding section, we discussed the advantages, limitations, and prospects (precisely with deep machine learning) of computational fluid dynamics in the clinical assessment and investigation of respiratory diseases.

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“…The application of AI has expanded prominently in the medical field due to advances in computing power, learning algorithms, data storage, and the availability of large-high-quality data sourced from electronic medical records and wearable health trackers [1,2]. Although its adoption is still in early phases, AI has been extensively used across many fields in medicine such as radiology [6,7], cardiology [8][9][10][11], dermatology [12][13][14][15], ophthalmology [16,17], neurology [18,19], oncology [20,21], gastroenterology [22,23], and respiratory medicine [24]. Some examples of clinical applications that have been approved by the US Food and Drug Administration (FDA) include Arterys for cardiac magnetic resonance image analysis, Idx for detection of diabetic retinopathy, and Mam-moScreen for breast cancer screening [25,26].…”

Section: Introductionmentioning

confidence: 99%

Artificial intelligence in arthroplasty

2021

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Artificial intelligence (AI) is altering the world of medicine. Given the rapid advances in technology, computers are now able to learn and improve, imitating humanoid cognitive function. AI applications currently exist in various medical specialties, some of which are already in clinical use. This review presents the potential uses and limitations of AI in arthroplasty to provide a better understanding of the existing technology and future direction of this field.Recent literature demonstrates that the utilization of AI in the field of arthroplasty has the potential to improve patient care through better diagnosis, screening, planning, monitoring, and prediction. The implementation of AI technology will enable arthroplasty surgeons to provide patient-specific management in clinical decision making, preoperative health optimization, resource allocation, decision support, and early intervention. While this technology presents a variety of exciting opportunities, it also has several limitations and challenges that need to be overcome to ensure its safety and effectiveness.

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

Cited by 106 publications

References 58 publications

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

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

Computational Fluid Dynamics Modeling in Respiratory Airways Obstruction: <i>Current Applications and Prospects</i>

Artificial intelligence in arthroplasty

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

Cited by 106 publications

References 58 publications

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

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

Computational Fluid Dynamics Modeling in Respiratory Airways Obstruction: &lt;i&gt;Current Applications and Prospects&lt;/i&gt;

Artificial intelligence in arthroplasty

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Computational Fluid Dynamics Modeling in Respiratory Airways Obstruction: <i>Current Applications and Prospects</i>