Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Artificial Intelligence in Cardiology
1.105
Zitationen
8
Autoren
2018
Jahr
Abstract
Artificial intelligence and machine learning are poised to influence nearly every aspect of the human condition, and cardiology is not an exception to this trend. This paper provides a guide for clinicians on relevant aspects of artificial intelligence and machine learning, reviews selected applications of these methods in cardiology to date, and identifies how cardiovascular medicine could incorporate artificial intelligence in the future. In particular, the paper first reviews predictive modeling concepts relevant to cardiology such as feature selection and frequent pitfalls such as improper dichotomization. Second, it discusses common algorithms used in supervised learning and reviews selected applications in cardiology and related disciplines. Third, it describes the advent of deep learning and related methods collectively called unsupervised learning, provides contextual examples both in general medicine and in cardiovascular medicine, and then explains how these methods could be applied to enable precision cardiology and improve patient outcomes.
Ähnliche Arbeiten
"Why Should I Trust You?"
2016 · 14.150 Zit.
A Comprehensive Survey on Graph Neural Networks
2020 · 8.543 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.047 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.410 Zit.
Analysis of Survival Data.
1985 · 4.379 Zit.