Key result
AI and machine learning show potential for diagnosing and predicting cardiovascular complications in COVID-19.
Why the study?
Cardiovascular manifestations of COVID-19 highlighted the need for fast, sensitive, and specific tools for early identification and risk stratification.
This review highlights the potential of machine learning and artificial intelligence to improve the detection and prognosis of cardiovascular complications in COVID-19 patients.
Answers are grounded in this paper and cite their sources.
May aid CV risk stratification in COVID-19; leaves open prospective validation before clinical adoption.
Since January 2020, coronavirus disease 2019 (COVID-19) has rapidly become a global concern, and its cardiovascular manifestations have highlighted the need for fast, sensitive and specific tools for early identification and risk stratification. Machine learning is a software solution with the ability to analyze large amounts of data and make predictions without prior programming. When faced with new problems with unique challenges as evident in the COVID-19 pandemic, machine learning can offer solutions that are not apparent on the surface by sifting quickly through massive quantities of data and making associations that may have been missed. Artificial intelligence is a broad term that encompasses different tools, including various types of machine learning and deep learning. Here, we review several cardiovascular applications of machine learning and artificial intelligence and their potential applications to cardiovascular diagnosis, prognosis, and therapy in COVID-19 infection.
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Zimmerman et al. (2020) conducted a review in COVID-19 with cardiovascular complications. Machine learning and artificial intelligence was evaluated. Machine learning and artificial intelligence techniques demonstrate potential utility in analyzing large datasets for the diagnosis, risk stratification, and prognosis of cardiovascular complications in COVID-19.
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