Steps to use artificial intelligence in echocardiography

Kusunose, Kenya

doi:10.1007/s12574-020-00496-4

Cited by 54 publications

(67 citation statements)

References 34 publications

(53 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In the future it is to be expected that AI solutions will increasingly support technicians and cardiologists in the field of digital care ( 64 , 65 ) and echocardiography ( 66 ). AI can be incorporated into everyday practice and become a valuable aid for cardiologists and technicians dealing with cardiovascular disease ( 67 , 68 ). AI will help to reduce workload, increase reproducibility and standardize data reporting.…”

Section: Discussionmentioning

confidence: 99%

Routine Echocardiography and Artificial Intelligence Solutions

Schuuring

Išgum

Cosyns³

et al. 2021

Front. Cardiovasc. Med.

View full text Add to dashboard Cite

Introduction: Echocardiography is widely used because of its portability, high temporal resolution, absence of radiation, and due to the low-costs. Over the past years, echocardiography has been recommended by the European Society of Cardiology in most cardiac diseases for both diagnostic and prognostic purposes. These recommendations have led to an increase in number of performed studies each requiring diligent processing and reviewing. The standard work pattern of image analysis including quantification and reporting has become highly resource intensive and time consuming. Existence of a large number of datasets with digital echocardiography images and recent advent of AI technology have created an environment in which artificial intelligence (AI) solutions can be developed successfully to automate current manual workflow.Methods and Results: We report on published AI solutions for echocardiography analysis on methods' performance, characteristics of the used data and imaged population. Contemporary AI applications are available for automation and advent in the image acquisition, analysis, reporting and education. AI solutions have been developed for both diagnostic and predictive tasks in echocardiography. Left ventricular function assessment and quantification have been most often performed. Performance of automated image view classification, image quality enhancement, cardiac function assessment, disease classification, and cardiac event prediction was overall good but most studies lack external evaluation.Conclusion: Contemporary AI solutions for image acquisition, analysis, reporting and education are developed for relevant tasks with promising performance. In the future major benefit of AI in echocardiography is expected from improvements in automated analysis and interpretation to reduce workload and improve clinical outcome. Some of the challenges have yet to be overcome, however, none of them are insurmountable.

show abstract

Section: Discussionmentioning

confidence: 99%

Routine Echocardiography and Artificial Intelligence Solutions

Schuuring

Išgum

Cosyns³

et al. 2021

Front. Cardiovasc. Med.

View full text Add to dashboard Cite

show abstract

“…It involves smart robots, cloud-based data, soft analysis, smart monitoring, etc., ultimately helping healthcare providers tackle cardiology cases with more impact. Figure 1 reflects the various advanced and well-proven tools and strategies offered while handling the cardiology cases, specifically during the toughest COVID-19 time [16] , [17] , [18] . Artificial intelligence's philosophy becomes effective when treating smart and intelligent sensors' powerful tools.…”

Section: Tools and Technologies Of Ai For Cardiology During Covid-19mentioning

confidence: 99%

“…The focus of this technology is to increase awareness in clinical practice. It reduces cost and increases the value of decision making, interpretation, and image acquisition [ 15 , 16 ]. With the help of an electronic health record, it provides a better opportunity for personalised therapy.…”

Section: Benefits Of Artificial Intelligence In Cardiologymentioning

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

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.

show abstract

“…In the intensive care unit, there are cases in which it is necessary to make a visual judgment of function using echocardiographic images due to time constraints. Recently, in an environment with a rapidly increasing number of confirmed/suspected COVID-19 patients, non-specialists, such as emergency physicians, are more likely required to perform this examination in the infection control room [ 6 ]. Development of an automatic analysis tool for echocardiographic images is desired as a decision support system.…”

Section: Introductionmentioning

confidence: 99%

How to standardize the measurement of left ventricular ejection fraction

et al. 2021

Self Cite

View full text Add to dashboard Cite

Despite recent advances in imaging for myocardial deformation, left ventricular ejection fraction (LVEF) is still the most important index for systolic function in daily practice. Its role in multiple fields (e.g., valvular heart disease, myocardial infarction, cancer therapy-related cardiac dysfunction) has been a mainstay in guidelines. In addition, assessment of LVEF is vital to clinical decision-making in patients with heart failure. However, notable limitations to LVEF include poor inter-observer reproducibility dependent on observer skill, poor acoustic windows, and variations in measurement techniques. To solve these problems, methods for standardization of LVEF by sharing reference images among observers and artificial intelligence for accurate measurements have been developed. In this review, we focus on the standardization of LVEF using reference images and automated LVEF using artificial intelligence.

show abstract

Steps to use artificial intelligence in echocardiography

Cited by 54 publications

References 34 publications

Routine Echocardiography and Artificial Intelligence Solutions

Routine Echocardiography and Artificial Intelligence Solutions

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

How to standardize the measurement of left ventricular ejection fraction

Contact Info

Product

Resources

About