Usefulness of machine learning in COVID-19 for the detection and prognosis of cardiovascular complications

Abstract

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.

Echocardiography in COVID-19 Pandemic

“…AI includes machine learning (ML), which offers the potential to improve the accuracy and reliability of echocardiography by combining clinician interpretation with information derived from ML algorithms. In conclusion, high volume data generated from cardiac imaging can be integrated in a multiparametric approach for pattern recognition and imaging data-based disease phenotype characterization, particularly useful and time-saving in the setting on COVID-19 pandemic 69 .…”

The Promise of AI in Detection, Diagnosis, and Epidemiology for Combating COVID-19: Beyond the Hype

“…The UK Biobank, one of the largest biobanks in the world in terms of data volume and depth including multi-organ imaging, is an example of one that has been integrated with pre-existing data of COVID-19 patients. UK Biobank's data has been used for research related to COVID-19 [for example, see Armstrong et al (2020) 2020), Kenneth and So (2020), Pereira et al (2020), Toh and Brody (2020), and Zimmerman and Kalra (2020), exist that have used biobanks' data for their development, and it is likely that the use of biobanks' data for the development of AI solutions will increase in the near future.…”

Machine Learning in Healthcare Communication

“…Coronavirus disease 2019 (COVID-19) has become a major global concern since January 2020. It primarily affects the cardiovascular system and requires sensitive, fast, and specific tools to identify the disease early, and better preventative measures can be applied [85]. COVID-19 is a worldwide crisis.…”