Designing Clinical Decision Support Systems with Users in Mind: Addressing Context Sensitivity, Explainability, and Data Visualization

Introduction: Clinical decision support systems (CDSS) offer great potential for improving the quality of care but have so far seen only limited adoption in clinical practice [ref:1]. A key barrier lies in their predominantly technology-driven development, which often fails to adequately account [for full text, please go to the a.m. URL]

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Publication Details

Journal
German Medical Science (German Research Foundation)
Published
2025-11-03
DOI
https://doi.org/10.3205/25gmds099
Primary Topic
Machine Learning in Healthcare
Type
article
Field-Weighted Citation Impact
0.00
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article

Designing Clinical Decision Support Systems with Users in Mind: Addressing Context Sensitivity, Explainability, and Data Visualization

German Medical Science (German Research Foundation)
Machine Learning in Healthcare
article

Designing Clinical Decision Support Systems with Users in Mind: Addressing Context Sensitivity, Explainability, and Data Visualization

article en

Abstract

Introduction: Clinical decision support systems (CDSS) offer great potential for improving the quality of care but have so far seen only limited adoption in clinical practice [ref:1]. A key barrier lies in their predominantly technology-driven development, which often fails to adequately account [for full text, please go to the a.m. URL]

German Medical Science (German Research Foundation)
University Hospital Carl Gustav Carus (DE)
Peace, Justice and strong institutions
Openalex Percentile: Top 23%
Machine Learning in Healthcare
DOIOpen Access PDFOpenAlex
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Designing Clinical Decision Support Systems with Users in Mind: Addressing Context Sensitivity, Explainability, and Data Visualization · German Medical Science (German Research Foundation) (2025) | TGRS Research Map | TGRS