Computational biology and bioinformatics articles within Nature Reviews Cardiology

Featured

  • Research Highlight |

    A wrist-worn, transdermal sensor can be used to measure plasma levels of cardiac troponin I, potentially facilitating the diagnosis of myocardial infarction.

    • Gregory B. Lim

  • Research Highlight |

    Researchers have engineered a wearable device that adheres to the skin and uses ultrasound imaging and a deep learning model to produce a dynamic, real-time assessment of cardiac function.

    • Gregory B. Lim

  • Review Article |

    Alternative splicing determines which exons are included in mature RNA and accounts for the majority of transcriptomic diversity. In this Review, Gotthardt and colleagues discuss how alternative splicing is regulated in the heart and how it differs in cardiac development, physiological adaptation and pathological remodelling. They also summarize technological advances in the field and potential applications of splicing data in cardiovascular medicine.

    • Michael Gotthardt
    • , Victor Badillo-Lisakowski
    •  & Leslie Leinwand

  • Review Article |

    Advances in machine learning technology in the past decade have accelerated the discovery of genetic loci associated with aortic disease. In this Review, Lindsay and colleagues discuss how emerging insights into the genetic architecture of aortic disease can improve the accuracy of disease prediction and facilitate the discovery of new therapeutic targets.

    • Elizabeth Chou
    • , James P. Pirruccello
    •  & Mark E. Lindsay

  • Research Highlight |

    A deep learning artificial intelligence algorithm applied to recordings from a digital stethoscope can be used to detect cardiac murmurs, aortic stenosis and mitral regurgitation with an accuracy that is similar to that of expert cardiologists.

    • Gregory B. Lim

  • Review Article |

    In this Review, Sermesant and colleagues discuss the applications of artificial intelligence (AI) in cardiovascular imaging and explain how pre-existing clinical knowledge can be included in AI methods to increase robustness. They also discuss the limitations of AI approaches in cardiovascular imaging and how they can be overcome.

    • Maxime Sermesant
    • , Hervé Delingette
    •  & Nicholas Ayache

  • News & Views |

    Valve replacement is currently the only treatment for calcific aortic valve disease. Studies of an uncommon, genetic form of aortic valve disease have yielded in vitro and mouse models of the disease and a transcriptomic disease signature. Machine learning-driven screens for compounds that normalize this signature promise to enable medical management of aortic valve disease.

    • Suya Wang
    •  & William T. Pu

  • Research Highlight |

    A new machine learning risk-stratification model accurately predicts the 1-year risk of ischaemic and major bleeding events in patients with an acute coronary syndrome and might be useful to guide clinical decision-making and optimize the quality of care of these patients.

    • Irene Fernández-Ruiz

  • Review Article |

    Advances in cardiovascular monitoring technologies have resulted in an influx of consumer-targeted wearable sensors that have the potential to detect numerous heart conditions. In this Review, Krittanawong and colleagues describe processes involved in biosignal acquisition and analysis of cardiovascular monitors, as well as their associated ethical, regulatory and legal challenges.

    • Chayakrit Krittanawong
    • , Albert J. Rogers
    •  & Sanjiv M. Narayan

  • Year in Review |

    Precision cardiology is a vision of a health-care approach that identifies the optimal course of care for each patient. Although precision cardiology is still in its nascent stage, new approaches and methodologies are being developed to achieve this goal and to overcome technical and implementation barriers. In 2018, several high-impact studies made progress in this direction.

    • Natalia Trayanova

  • Review Article |

    This Review summarizes the mechanisms of ectopic calcification processes in the cardiovascular system, with an emphasis on emerging knowledge obtained from advances in imaging methods, experimental models and multiomics-generated big data. This Review highlights the potential and challenges of artificial intelligence, machine learning and deep learning to integrate imaging and mechanistic data to identify biomarkers and effective treatments for cardiovascular calcification

    • Maximillian A. Rogers
    •  & Elena Aikawa

  • Review Article |

    Computational models are increasingly used in cardiology to integrate multiple data sets from individual patients and create virtual-patient simulations. In this Review, Niederer and colleagues discuss how multi-scale models of cardiac electrophysiology and mechanics can support diagnostic assessment and clinical decision-making and pave the way to personalized cardiac care.

    • Steven A. Niederer
    • , Joost Lumens
    •  & Natalia A. Trayanova

  • Review Article |

    Big data analytics have tremendous potential to improve cardiovascular quality of care and patient outcomes. In this Review, Rumsfeld and colleagues provide an overview of the data sources and methods that comprise big data analytics, describe the potential applications of these analyses in cardiovascular care and research, and delineate the principal challenges to implementing big data applications in cardiovascular practice.

    • John S. Rumsfeld
    • , Karen E. Joynt
    •  & Thomas M. Maddox

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