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Current Treatment Options in Cardiovascular Medicine

Erschienen in:

01.03.2020 | State-of-the-Arts Informatics (C Stultz, Section Editor)

Clinical Inference From Cardiovascular Imaging: Paradigm Shift Towards Machine-Based Intelligent Platform

verfasst von: Karthik Seetharam, MD, Nobuyuki Kagiyama, MD, PhD, Sirish Shrestha, MSc, Partho P Sengupta, MD, DM

Erschienen in: Current Treatment Options in Cardiovascular Medicine | Ausgabe 3/2020

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Abstract

Purpose of review

Diagnostic imaging plays an indispensable role in the modern management of cardiovascular diseases. Despite significant advances in imaging modalities, the workflow in clinical imaging requires a great deal of human input. With increasing demands in patient care, current workflows in cardiovascular imaging face a number of challenges which include insufficient number of specialists, time constraints, learning curves, and inter-observer variability.

Recent findings

Automated techniques using revolutionary approaches with machine learning can fundamentally alter our interpretation process and produce smarter, faster, and efficient results. With the emergence of big data and deep learning techniques which enable direct inference of image data without intensive feature engineering or can process raw images directly. Machine learning has been rapidly adopted in the field of medicine and has shown its fast and reproducible automatic inference in various cardiovascular imaging modalities, including echocardiography, nuclear imaging, cardiac computed tomography, and cardiac magnetic resonance.

Summary

While deep domain knowledge of cardiovascular disease remains the cornerstone throughout the process, physicians may be relieved from mundane tasks using automation and be able to spend more time on decision-making and communication with patients and other medical staff in the new paradigm brought by machine learning. In this review article, we explore the role of machine in the clinical inference from cardiac imaging data recently.

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Titel: Clinical Inference From Cardiovascular Imaging: Paradigm Shift Towards Machine-Based Intelligent Platform
verfasst von: Karthik Seetharam, MD
Nobuyuki Kagiyama, MD, PhD
Sirish Shrestha, MSc
Partho P Sengupta, MD, DM
Publikationsdatum: 01.03.2020
Verlag: Springer US
Erschienen in: Current Treatment Options in Cardiovascular Medicine / Ausgabe 3/2020
Print ISSN: 1092-8464
Elektronische ISSN: 1534-3189
DOI: https://doi.org/10.1007/s11936-020-0805-5

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Clinical Inference From Cardiovascular Imaging: Paradigm Shift Towards Machine-Based Intelligent Platform