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Bringing Data-Driven Process Analysis into Surgical Practice - the Surgical Process Analyzer


Martin Wagner, Tobias Weller, Lena-Marie Ternes, Rudolf Rempel, Maria MaleshkovaYork Sure-Vetter, Hannes Kenngott



Published: 2016 Juni

Buchtitel: Proceedings Surgical Data Science
Seiten: 6
Verlag: Springer
Erscheinungsort: Heidelberg
Organisation: Surgical Data Science
Referierte Veröffentlichung
BibTeX

Kurzfassung
The growing number of connected medical devices in the operating room and electronic health records provide valuable data to analyze surgical processes for workflow optimization, context-aware assistance systems and prediction of adverse events. In this area of surgical data science, i.e. surgical process analysis, a key challenge is to combine methods from computer science and statistics with surgical knowledge about processes and data, such as standard operating procedures, surgical guidelines, uncertainty and quality of data. We propose a novel framework that integrates handling of data, knowledge models and data analysis with an intuitive user interface for data visualization, process analytics and knowledge capturing. A key goal of this so called “Surgical Process Analyzer” is to empower surgical domain experts to perform process analysis in their surgical practice. As a result we expect to advance research in surgical data science by addressing real-world use-cases with collaboration of surgeons and data scientists that provides benefit for patients.

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Forschungsgruppe

Web Science und Wissensmanagement


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