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Clinician Preimplementation Perspectives of a Decision-Support Tool for the Prediction of Cardiac Arrhythmia Based on Machine Learning: Near-Live Feasibility and Qualitative Study
BACKGROUND: Artificial intelligence (AI), such as machine learning (ML), shows great promise for improving clinical decision-making in cardiac diseases by outperforming statistical-based models. However, few AI-based tools have been implemented in cardiology clinics because of the sociotechnical cha...
Autores principales: | Matthiesen, Stina, Diederichsen, Søren Zöga, Hansen, Mikkel Klitzing Hartmann, Villumsen, Christina, Lassen, Mats Christian Højbjerg, Jacobsen, Peter Karl, Risum, Niels, Winkel, Bo Gregers, Philbert, Berit T, Svendsen, Jesper Hastrup, Andersen, Tariq Osman |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8665383/ https://www.ncbi.nlm.nih.gov/pubmed/34842528 http://dx.doi.org/10.2196/26964 |
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