Acta Scientific Medical Sciences (ASMS)(ISSN: 2582-0931)

Research Article Volume 7 Issue 3

Non-invasive Predictive AI Coronary Angiography

TP Abdualimov1* and AG Obrezan1,2

1Department of General Practice and Therapy, My Medical Center, Saint-Petersburg, Russian Federation
2Department of Hospital Therapy, St. Petersburg State University, Saint-Petersburg, Russian Federation

*Corresponding Author: TP Abdualimov, Department of General Practice and Therapy, My Medical Center, Saint-Petersburg, Russian Federation.

Received: January 27, 2023; Published: February 16, 2023

Abstract

A novel approach to diagnosing coronary artery disease was proposed. A model for diagnosing coronary heart disease was designed using neural network analysis and allow to reveal transient myocardial ischemia, pathology of the main coronary arteries. The aim of the study was to compare the accuracy of the trained neural network model on the input structured data (sex and age, cholesterol levels, presence of chronic diseases, hereditary factors, lifestyle and etc.) and ECG images with the results of traditional coronary angiography. The proposed diagnostic model was proved to be reliable and highly sensitive for 1500150 cases. The model was compared with the traditional diagnostic methods of transient myocardial ischemia (24-hour Holter monitoring, treadmill test), where the presented diagnostic model was considered to be significantly effective. The accuracy of forecasts was assessed and justified by the cardiologists supervising patients with ACS on a daily basis. The study also presents a new method of sample extrapolation using generative adversarial networks allowing to exceed the volume of observations used in classical meta-analyses.

Keywords: Coronary Arteries; Neural Networks; Artificial Intelligence; Coronary Heart Disease; Deep Learning; ECG; Non-invasive Predictive AI Coronary Angiography

References

  1. Kuo FC., et al. “The relative utilities of genome-wide, gene panel, and individual gene sequencing in clinical practice”. Blood 130 (2017): 433-439.
  2. Muse ED., et al. “Towards a smart medical home”. Lancet 389 (2017): 358.
  3. Steinhubl SR., et al. “The emerging field of mobile health”. Science Translational Medicine 7 (2015): 283rv3.
  4. Shameer K., et al. “Translational bioinformatics in the era of real-time biomedical, health care and wellness data streams”. Brief Bioinformation 18 (2017): 105-124.
  5. Konstam MA., et al. “The academic medical system: reinvention to survive the revolution in health care”. Journal of the American College of Cardiology 69 (2017): 1305-1312.
  6. Steinhubl SR and Topol EJ. “Moving from digitalization to digitization in cardiovascular care: why is it important, and what could it mean for patients and providers?” Journal of the American College of Cardiology 66 (2015): 1489-1496.
  7. Boeldt DL., et al. “How consumers and physicians view new medical technology: comparative survey”. Journal of Medical Internet Research 17 (2015): e215.
  8. Vysotskaya ZhM and Terzov AI. “Mathematical models of non-invasive determination of coronary artery lesions in patients with coronary heart disease”. On Sat. New applications of morphometry and mathematical modeling in biomedical research. Kharkov, (1990): 53.
  9. Bala YuM., et al. “Mathematical approach to automatic diagnosis of ischemic heart disease”. On Sat. Computerization in medicine. Voronezh, (1990): 66–70.
  10. A Waheed., et al. “CovidGAN: Data Augmentation Using Auxiliary Classifier GAN for Improved Covid-19 Detection”. in IEEE Access 8 (2020): 91916-91923.

Citation

Citation: TP Abdualimov and AG Obrezan. “Non-invasive Predictive AI Coronary Angiography”.Acta Scientific Medical Sciences 7.3 (2023): 123-132.

Copyright

Copyright: © 2022 TP Abdualimov and AG Obrezan. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.




Metrics

Acceptance rate30%
Acceptance to publication20-30 days
Impact Factor1.403

Indexed In





News and Events


  • Certification for Review
    Acta Scientific certifies the Editors/reviewers for their review done towards the assigned articles of the respective journals.
  • Submission Timeline for Upcoming Issue
    The last date for submission of articles for regular Issues is April 30th, 2024.
  • Publication Certificate
    Authors will be issued a "Publication Certificate" as a mark of appreciation for publishing their work.
  • Best Article of the Issue
    The Editors will elect one Best Article after each issue release. The authors of this article will be provided with a certificate of "Best Article of the Issue".
  • Welcoming Article Submission
    Acta Scientific delightfully welcomes active researchers for submission of articles towards the upcoming issue of respective journals.

Contact US