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5 results on '"Schrodt, Jens"'

2. Ähnlichkeitsanalyse temporaler Patientengrafen mit Hilfe grafenbasierter Vergleichsalgorithmen

Author

Schrodt, Jens, Knaup, Petra, and Ganzinger, Matthias

Subjects
Entscheidungsunterstützung, ddc: 610, temporaler Graf, Grafen Theorie, 610 Medical sciences, Medicine, MIMIC-III, NetSimile, individueller Patientengraf, Grafenvergleich
Abstract

Einleitung: Die Grafentheorie ist ein weit gefasstes Teilgebiet der Mathematik, das von unterschiedlichen Disziplinen wie der Physik, Mathematik, Soziologie, Informatik sowie der Populationsbiologie- und Molekularbiologie [ref:1], [ref:2] genutzt wird, um verschiedene Sachverhalte[zum vollständigen Text gelangen Sie über die oben angegebene URL], 64. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS)

Published
2019

3. A Concept for Graph-Based Temporal Similarity of Patient Data.

Author

Ganzinger, Matthias, Schrodt, Jens, and Knaup, Petra

Subjects
DECISION support systems, SEPSIS, ELECTRONIC health records, CASE-based reasoning, GRAPH theory
Abstract

Computer-based decision support systems are often used for dedicated tasks such as the detection of sepsis. However, positive predictive values for sepsis detection are reported to achieve only around 46%. In this paper we describe a novel approach to use temporal data of electronic patient records based on similarity measures. We apply the concept of casebased reasoning, which is well-established in many fields of medical informatics. Temporal patient data are organized in a time-graph structure. For the quantification of similarity between cases, we exploit graph theory based approaches. For development and evaluation of our time-graph similarity frame we use the open MIMIC III dataset. In a later phase, we envision to transfer our concept from sepsis to other diseases. [ABSTRACT FROM AUTHOR]

Published
2019
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5. A Concept for Graph-Based Temporal Similarity of Patient Data.

Author

Ganzinger M, Schrodt J, and Knaup P

Subjects
Electronic Health Records, Expert Systems, Humans, Software, Medical Informatics
Abstract

Computer-based decision support systems are often used for dedicated tasks such as the detection of sepsis. However, positive predictive values for sepsis detection are reported to achieve only around 46%. In this paper we describe a novel approach to use temporal data of electronic patient records based on similarity measures. We apply the concept of case-based reasoning, which is well-established in many fields of medical informatics. Temporal patient data are organized in a time-graph structure. For the quantification of similarity between cases, we exploit graph theory based approaches. For development and evaluation of our time-graph similarity frame we use the open MIMIC III dataset. In a later phase, we envision to transfer our concept from sepsis to other diseases.

Published
2019
Full Text
View/download PDF

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