Current applications of big data and machine learning in cardiology
Renato Cuocolo
Teresa Perillo
Eliana De Rosa
Lorenzo Ugga
Mario Petretta
摘要：Machine learning (ML) is a software solution with the ability of making predictions without prior explicit programming,aiding in the analysis of large amounts of data.These algorithms can be trained through supervised or unsupervised learning.Cardiology is one of the fields of medicine with the highest interest in its applications.They can facilitate every step of patient care,reducing the margin of error and contributing to precision medicine.In particular,ML has been proposed for cardiac imaging applications such as automated computation of scores,differentiation of prognostic phenotypes,quantification of heart function and segmentation of the heart.These tools have also demonstrated the capability of performing early and accurate detection of anomalies in electrocardiographic exams.ML algorithms can also contribute to cardiovascular risk assessment in different settings and perform predictions of cardiovascular events.Another interesting research avenue in this field is represented by genomic assessment of cardiovascular diseases.Therefore,ML could aid in making earlier diagnosis of disease,develop patient-tailored therapies and identify predictive characteristics in different pathologic conditions,leading to precision cardiology.
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论文发表日期：2019-01-01
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：7( 601-607 )
英文信息