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01-08-2021 | Artificial Intelligence | Editor's Page

Artificial intelligence in nuclear cardiology: Preparing for the fifth industrial revolution

Author: Ernest V. Garcia, PhD

Published in: Journal of Nuclear Cardiology | Issue 4/2021

Excerpt

“The past is but the beginning of a beginning, and all that is or has been is but the twilight of the dawn.” HG Wells, The Discovery of the Future (1913)

…

Bridgman R, Are you ready for the 5th industrial revolution? (2019) https://www.recruitment-international.co.uk/blog/2019/10/are-you-ready-for-the-5th-industrial-revolution. Accessed May 3, 2021.

The Fifth Industrial revolution and how it will change the business landscape, REGENESYS (2020). https://insights.regenesys.net/the-fifth-industrial-revolution-5ir/ Accessed May 3, 2021.

DePuey EG, Mahmarian JJ, Miller TD, et al. Patient-centered imaging. J Nucl Cardiol 2012;19:185-215. https://doi.org/10.1007/s12350-012-9523-z.CrossRefPubMed

Garcia E. My Ride to the Cloud. TEDx Talks, (2017). Accessed May 3, 2021. https://www.youtube.com/watch?v=Tiwcc2opa04

LeCun Y, Bengio Y, Hinton G. Deep learning. Nature 2015;521:436-44.CrossRef

Arnold Z. What investment trends reveal about the global AI landscape (2020). https://www.brookings.edu/techstream/what-investment-trends-reveal-about-the-global-ai-landscape Accessed May 3, 2021.

Song C, Yang Y, Wernick MN, et al. Low-dose cardiac-gated SPECT studies using a residual convolutional neural network. 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019), 2019, 653-656.

Shiri I, Sabet KA, Arabi H, et al. Standard SPECT myocardial perfusion estimation from half-time acquisitions using deep convolutional residual neural networks. J Nucl Cardiol 2020. https://doi.org/10.1007/s12350-020-02119-y.CrossRefPubMed

Ramon AJ, Yang Y, Pretorius PH, et al. Improving diagnostic accuracy in low-dose SPECT myocardial perfusion imaging with convolution denoising networks. IEEE Trans Med Imaging 2020;39:2893-903.CrossRef

10.

Shi L, Onofrey JA, Liu H, et al. Deep learning-based attenuation map generation for myocardial perfusion SPECT. Eur J Nucl Med Mol Imaging 2020;47:2383-95. https://doi.org/10.1007/s00259-020-04746-6.CrossRefPubMed

11.

Wang T, Lei Y, Tang H, et al. A learning-based automatic segmentation and quantification method of left ventricle in gated myocardial perfusion SPECT imaging: A feasibility study. J Nucl Cardiol 2020;27:976-87.CrossRef

12.

Betancur J, Rubeaux M, Fuchs TA, et al. Automatic valve plane localization in myocardial perfusion SPECT/CT by machine learning: Anatomic and clinical validations. J Nucl Med 2017;58:961-7.CrossRef

13.

Garcia EV, Klein JL, Moncayo V, et al. Diagnostic performance of an artificial intelligence-driven cardiac-structured reporting system for myocardial perfusion SPECT imaging. J. Nucl. Cardiol 2020;27:1652-64. https://doi.org/10.1007/s12350-018-1432-3.CrossRefPubMed

14.

Betancur J, Hu LH, Commandeur F, et al. Deep learning analysis of upright-supine high-efficiency SPECT myocardial perfusion imaging for prediction of coronary artery disease: A multicenter study. J Nucl Med 2019;60:664-70.CrossRef

15.

Juarez-Orozco LE, Knol RJJ, Sanches-Catasus CA, et al. Machine learning in the integration of simple variables for identifying patients with myocardial ischemia. J Nucl Cardiol 2020;27:147-55.CrossRef

16.

Alonso DH, Wernick MN, Yang Y, et al. Prediction of cardiac death after adenosine myocardial perfusion SPECT based on machine learning. J Nucl Cardiol 2019;26:1746-54.CrossRef

17.

Betancur J, Otaki Y, Motwani M, et al. Prognostic value of combined clinical and myocardial perfusion imaging data using machine learning. JACC Cardiovasc Imaging 2018;11:1000-9.CrossRef

18.

Lin A, Kolossváry M, Išgum S, Maurovich-Horvat P, et al. Artificial intelligence: Improving the efficiency of cardiovascular imaging. Exp Rev Med Devices 2020;17(6):565-77. https://doi.org/10.1080/17434440.2020.1777855.CrossRef

19.

Slart RHJA, Williams MC, Juarez-Orozco LE, et al. Position paper of the EACVI and EANM on artificial intelligence applications in multimodality cardiovascular imaging using SPECT/CT, PET/CT, and cardiac CT. Eur J Nucl Med Mol Imaging 2021. https://doi.org/10.1007/s00259-021-05341-z.CrossRefPubMedPubMedCentral

20.

Sung J, Stewart CL, Freedman B. Artificial intelligence in health care: Preparing for the fifth Industrial Revolution. MJA 2020. https://doi.org/10.5694/mja2.50755.CrossRefPubMed

21.

Ornstein C, Thomas K. Sloan Kettering’s cozy deal with start-up ignites a new uproar. New York Times. https://www.nytimes.com/2018/09/20/health/memorial-sloan-kettering-cancer-paige-ai.html. Published September 20, 2018. Accessed May 5, 2021.

22.

Larson DB, Magnus DC, Lungren MP, Shah NH, Langlotz CP. Ethics of using and sharing clinical imaging data for artificial intelligence: A proposed framework. Radiology 2020;295:675-82.CrossRef

23.

Copeland R. Google’s ‘Project Nightingale’ gathers personal health data on millions of Americans. Wall Street Journal. https://www.wsj.com/articles/google-s-secret-project-nightingale-gathers-personal-health-data-on-millionsof-americans-11573496790?mod=article_inline. Published November 11, 2019. Accessed May 5, 2021.

24.

Artificial Intelligence/Machine Learning (AI/ML)-Based software as a medical device (SaMD) Action Plan (2021) https://www.fda.gov/media/145022/download Accessed May 5, 2021

25.

Proposed Regulatory Framework for Modifications to Artificial Intelligence/Machine Learning (AI/ML)-Based Software as a Medical Device (SaMD) - Discussion Paper and Request for Feedback. (2019) https://www.fda.gov/media/122535/download Accessed May 5, 2021

26.

Skloot R. The Immortal Life of Henrietta Lacks. New York, NY: Penguin Random House; 2010.

27.

Tobia K, Nielsen A, Stremitzer S. When does physician use of AI increase liability? J Nucl Med 2021;62:17-21. https://doi.org/10.2967/jnumed.120.256032.CrossRefPubMed

28.

Faden RR, Kass NE, Goodman SN, Pronovost P, Tunis S, Beauchamp TL. An ethics framework for a learning health care system: A departure from traditional research ethics and clinical ethics. Hastings Cent Rep 2013;43:S16-27.CrossRef

Title: Artificial intelligence in nuclear cardiology: Preparing for the fifth industrial revolution
Author: Ernest V. Garcia, PhD
Publication date: 01-08-2021
Publisher: Springer International Publishing
Keyword: Artificial Intelligence
Published in: Journal of Nuclear Cardiology / Issue 4/2021
Print ISSN: 1071-3581
Electronic ISSN: 1532-6551
DOI: https://doi.org/10.1007/s12350-021-02671-1

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