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Big Data and AI in Cardiac Imaging

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Trends of Artificial Intelligence and Big Data for E-Health

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Abstract

Cardiac imaging is of paramount importance in the diagnosis and management of patients with heart disease. Multiple modalities are encompassed within cardiac imaging, including echocardiography, magnetic resonance imaging (MRI), computed tomography (CT), and nuclear medicine. All of the modalities are primed to utilize artificial intelligence to increase accuracy, efficiency, and discover novel relationships between disease and outcomes. Artificial intelligence in cardiac imaging can improve multiple sections in the imaging process: acquisition, optimization, measurements, interpretation, and decision support. Important strides forward have already been made in each of the modalities; some have shown the ability to automatically diagnose disease, others to improve efficiency of clinical workflow, and still others to predict morbidity. Reproducibility and challenges with deployment remain barriers to widespread use of artificial intelligence in cardiac imaging, but the road ahead shows promise.

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Authors and Affiliations

  1. Stanford University, Lucile Packard Children’s Hospital, 750 Welch Rd, Ste 305, Palo Alto, CA, 94034, USA

    Charitha D. Reddy

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  1. Charitha D. Reddy
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Correspondence to Charitha D. Reddy .

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Editors and Affiliations

  1. National School of Computer Science (ENSI), Manouba University, COSMOS Laboratory, Manouba, Tunisia

    Houneida Sakly

  2. Department of Radiology, Stanford University, Palo Alto, CA, USA

    Kristen Yeom

  3. Northwestern University, Chicago, IL, USA

    Safwan Halabi

  4. Radiologist and Associate Professor in medical Imaging, Carthage Medical International Center Monastir and Sousse Medina Medical Imaging Center, Monastir, Tunisia

    Mourad Said

  5. Department Radiology, Stanford Medicine, Palo Alto, CA, USA

    Jayne Seekins

  6. National School of Computer Science (ENSI), Manouba University, COSMOS Laboratory, Manouba, Tunisia

    Moncef Tagina

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Reddy, C.D. (2022). Big Data and AI in Cardiac Imaging. In: Sakly, H., Yeom, K., Halabi, S., Said, M., Seekins, J., Tagina, M. (eds) Trends of Artificial Intelligence and Big Data for E-Health. Integrated Science, vol 9. Springer, Cham. https://doi.org/10.1007/978-3-031-11199-0_5

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