Combining Machine Learning With Real-World Data to Identify Gaps in Clinical Practice Guidelines: Feasibility Study Using the Prospective German Stroke Registry and the National Acute Ischemic Stroke Guidelines

Combining Machine Learning With Real-World Data to Identify Gaps in Clinical Practice Guidelines: Feasibility Study Using the Prospective German Stroke Registry and the National Acute Ischemic Stroke Guidelines

Abstract BackgroundClinical practice guidelines (CPGs) serve as essential tools for guiding clinicians in providing appropriate patient care. However, clinical practice does not always reflect CPGs. This is particularly critical in acute diseases requiring immediate treatment,...

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Main Authors: Sandrine Müller, Susanne Diekmann, Markus Wenzel, Horst Karl Hahn, Johannes Tuennerhoff, Ulrike Ernemann, Florian Hennersdorf, Max Westphal, Sven Poli
Format: Article
Language:English
Published: JMIR Publications 2025-07-01
Series:JMIR Medical Informatics
Online Access:https://medinform.jmir.org/2025/1/e69282
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https://medinform.jmir.org/2025/1/e69282

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