Artificial intelligence in pulmonary medicine: computer vision, predictive model and COVID-19

Khemasuwan, Danai; Sorensen, Jeffrey; Colt, Henri G.

doi:10.1183/16000617.0181-2020

Cited by 65 publications

(31 citation statements)

References 90 publications

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“…The world is presently suffering from the disastrous impacts of COVID-19 pandemic; this has directly affected the healthcare system and its associated fields. There is a requirement to effectively analyse the large amount of data produced during this global crisis, and AI can do it [25] , [26] , [27] . AI analyses the raw data and mines the same to derive a meaningful conclusion.…”

Section: Significant Capabilities Of Ai For Taking the Challenges Of mentioning

confidence: 99%

Applications of Artificial Intelligence (AI) for cardiology during COVID-19 pandemic

Haleem¹,

Javaid²,

Singh³

et al. 2021

Sustainable Operations and Computers

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Background and aims Artificial Intelligence (AI) shows extensive capabilities to impact different healthcare areas during the COVID-19 pandemic positively. This paper tries to assess the capabilities of AI in the field of cardiology during the COVID-19 pandemic. This technology is useful to provide advanced technology-based treatment in cardiology as it can help analyse and measure the functioning of the human heart. Methods We have studied a good number of research papers on Artificial Intelligence on cardiology during the COVID-19 pandemic to identify its significant benefits, applications, and future scope. AI uses artificial neuronal networks (ANN) to predict. In cardiology, it is used to predict the survival of a COVID-19 patient from heart failure. Results AI involves complex algorithms for predicting somewhat successful diagnosis and treatments. This technology uses different techniques, such as cognitive computing, deep learning, and machine learning. It is incorporated to make a decision and resolve complex challenges. It can focus on a large number of diseases, their causes, interactions, and prevention during the COVID-19 pandemic. This paper introduces AI-based care and studies its need in the field of cardiology. Finally, eleven major applications of AI in cardiology during the COVID-19 pandemic are identified and discussed. Conclusions Cardiovascular diseases are one of the major causes of death in human beings, and it is increasing for the last few years. Cardiology patients' treatment is expensive, so this technology is introduced to provide a new pathway and visualise cardiac anomalies. AI is used to identify novel drug therapies and improve the efficiency of a physician. It is precise to predict the outcome of the COVID-19 patient from cardiac-based algorithms. Artificial intelligence is becoming a popular feature of various engineering and healthcare sectors, is thought for providing a sustainable treatment platform. During the COVID-19 pandemic, this technology digitally controls some processes of treatments.

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Section: Significant Capabilities Of Ai For Taking the Challenges Of mentioning

confidence: 99%

Applications of Artificial Intelligence (AI) for cardiology during COVID-19 pandemic

Haleem¹,

Javaid²,

Singh³

et al. 2021

Sustainable Operations and Computers

View full text Add to dashboard Cite

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“…The last layer is a fully connected output layer which provides final probabilities for each label as a final classification (figure 2). 6 CNN has achieved remarkable performance and accuracy in various imaging applications through training on existing datasets. However, most of the published studies used relatively small datasets (<1000 CXR images of COVID-19 cases).…”

Section: Detection Of Covid-19 On Medical Imagingmentioning

confidence: 99%

Applications and challenges of AI-based algorithms in the COVID-19 pandemic

Khemasuwan

Colt

2021

BMJ Innov

Self Cite

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The COVID-19 pandemic is shifting the digital transformation era into high gear. Artificial intelligence (AI) and, in particular, machine learning (ML) and deep learning (DL) are being applied on multiple fronts to overcome the pandemic. However, many obstacles prevent greater implementation of these innovative technologies in the clinical arena. The goal of this narrative review is to provide clinicians and other readers with an introduction to some of the concepts of AI and to describe how ML and DL algorithms are being used to respond to the COVID-19 pandemic. First, we describe the concept of AI and some of the requisites of ML and DL, including performance metrics of commonly used ML models. Next, we review some of the literature relevant to outbreak detection, contact tracing, forecasting an outbreak, detecting COVID-19 disease on medical imaging, prognostication and drug and vaccine development. Finally, we discuss major limitations and challenges pertaining to the implementation of AI to solve the real-world problem of the COVID-19 pandemic. Equipped with a greater understanding of this technology and AI’s limitations, clinicians may overcome challenges preventing more widespread applications in the clinical management of COVID-19 and future pandemics.

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“…Artificial intelligence, including machine learning, is an interesting area of research which has been given a lot of attention during the last years. Machine learning algorithms and other artificial intelligence approaches may be trained to recognize underlaying relationships in a dataset and thereby perform tasks such as classification, recognition, and counting of lung nodules on chest CT to predict cancer risk and navigate clinical decision options (Khemasuwan et al, 2020). This approach has also been tested in an attempt to characterize MSCs as a step forward toward improved MSC manufacturing process and a better MSC cell product.…”

Section: Predicting the Best Suited Mesenchymal Stromal Cells Cell Prmentioning

confidence: 99%

Research Progress on Strategies that can Enhance the Therapeutic Benefits of Mesenchymal Stromal Cells in Respiratory Diseases With a Specific Focus on Acute Respiratory Distress Syndrome and Other Inflammatory Lung Diseases

et al. 2021

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Recent advances in cell based therapies for lung diseases and critical illnesses offer significant promise. Despite encouraging preclinical results, the translation of efficacy to the clinical settings have not been successful. One of the possible reasons for this is the lack of understanding of the complex interaction between mesenchymal stromal cells (MSCs) and the host environment. Other challenges for MSC cell therapies include cell sources, dosing, disease target, donor variability, and cell product manufacturing. Here we provide an overview on advances and current issues with a focus on MSC-based cell therapies for inflammatory acute respiratory distress syndrome varieties and other inflammatory lung diseases.

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Artificial intelligence in pulmonary medicine: computer vision, predictive model and COVID-19

Cited by 65 publications

References 90 publications

Applications of Artificial Intelligence (AI) for cardiology during COVID-19 pandemic

Applications of Artificial Intelligence (AI) for cardiology during COVID-19 pandemic

Applications and challenges of AI-based algorithms in the COVID-19 pandemic

Research Progress on Strategies that can Enhance the Therapeutic Benefits of Mesenchymal Stromal Cells in Respiratory Diseases With a Specific Focus on Acute Respiratory Distress Syndrome and Other Inflammatory Lung Diseases

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