AI Article Synopsis
- Recent developments in machine learning (ML) enable the automated analysis of complex data types, like text, images, and sounds, by understanding intricate patterns within that data.
- Cardiovascular medicine stands to benefit significantly from these ML advancements due to the extensive digitization of medical records and numerous diagnostic tests for heart-related diseases.
- The article highlights successful ML applications in cardiovascular diagnostics, showcasing how these technologies can automate interpretations, enhance measurement accuracy, and predict new diagnoses using less invasive tests.
Article Abstract
Recent advances in machine learning (ML) have made it possible to analyze high-dimensional and complex data-such as free text, images, waveforms, videos, and sound-in an automated manner by successfully learning complex associations within these data. Cardiovascular medicine is particularly well poised to take advantage of these ML advances, due to the widespread digitization of medical data and the large number of diagnostic tests used to evaluate cardiovascular disease. Various ML approaches have successfully been applied to cardiovascular tests and diseases to automate interpretation, accurately perform measurements, and, in some cases, predict novel diagnoses from less invasive tests, effectively expanding the utility of more widely accessible diagnostic tests. Here, we present examples of some impactful advances in cardiovascular medicine using ML across a variety of modalities, with a focus on deep learning applications.
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Source |
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9798021 | PMC |
| http://dx.doi.org/10.1016/j.xcrm.2022.100869 | DOI Listing |
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