The Application of Machine Learning to Quality Improvement Through the Lens of the Radiology Value Network.

Clicks: 315
ID: 39928
2019
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Ranked #9 of 22 articles by views in journal of the american college of radiology : jacr

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Abstract
Recent advances in machine learning and artificial intelligence offer promising applications to radiology quality improvement initiatives as they relate to the radiology value network. Coordination within the interlocking web of systems, events, and stakeholders in the radiology value network may be mitigated though standardization, automation, and a focus on workflow efficiency. In this article the authors present applications of these various strategies via use cases for quality improvement projects at different points in the radiology value network. In addition, the authors discuss opportunities for machine-learning applications in data aggregation as opposed to traditional applications in data extraction.
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makeeva2019thejournal Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Makeeva, Valeria;Gichoya, Judy;Hawkins, C Matthew;Towbin, Alexander J;Heilbrun, Marta;Prater, Adam;
Journal journal of the american college of radiology : jacr
Year 2019
DOI
S1546-1440(19)30639-8
URL
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