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Applications of Artificial Intelligence in Cardiovascular Emergencies – Status Quo and Outlook Cover

Abstract

Cardiovascular diseases are the leading cause of death, with many lives being affected by critical emergencies like heart attacks, strokes, and other acute conditions. Recognizing the early warning signs is crucial for highlighting the need for immediate medical attention, especially since a quick intervention may significantly improve short and long-term patient outcome. Artificial intelligence (AI) has become a key technology in healthcare, and especially in the cardiovascular field. AI, and in particular deep learning is well suited for automatically analyzing medical images, signals, and data. Its success rests on the availability of large amounts of curated data, and the access to high performance computing infrastructures for training the deep-learning algorithms. Thus, in cardiovascular care, AI plays a dynamic role in disease detection, predicting disease outcome, and guiding treatment decisions. This review paper details and discusses the current role of AI for the most common cardiovascular emergencies. It provides insight into the specific issues, risk factors, different subtypes of the diseases, and algorithms developed to date, followed by an outlook.

DOI: https://doi.org/10.2478/jce-2023-0019 | Journal eISSN: 2457-5518 | Journal ISSN: 2457-550X
Language: English
Page range: 83 - 102
Submitted on: Nov 1, 2023
Accepted on: Nov 28, 2023
Published on: Dec 10, 2023
Published by: Asociatia Transilvana de Terapie Transvasculara si Transplant KARDIOMED
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2023 Cosmin-Andrei Hatfaludi, Manuela-Daniela Danu, Horia-Andrei Leonte, Andreea-Bianca Popescu, Florin Condrea, Gabriela-Dorina Aldea, Andreea-Elena Sandu, Marius Leordeanu, Constantin Suciu, Ioana-Patricia Rodean, Lucian-Mihai Itu, published by Asociatia Transilvana de Terapie Transvasculara si Transplant KARDIOMED
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.